A is for Assessing your infrastructure

You need to understand all the elements that comprise your infrastructure—the hardware, software, networks, and applications—and how they work interdependently and can affect performance and availability.

B is for Building a performance management strategy

Your business has a strategy, so why would you leave your infrastructure—which is a critical driver for that strategy—rudderless? You need to set performance targets, establish performance baselines, identify KPIs to measure and monitor, and define the roles and responsibilities of different stakeholders, including IT staff, business users, and external vendors.

C is for Continuous monitoring and improvement

Once you’ve mapped out how your infrastructure should perform, you need to ensure that it’s meeting those expectations on an ongoing basis. This requires tools and techniques to monitor performance in real time, identify issues, and troubleshoot problems. And because change is constant, you need to continuously optimize your infrastructure to improve performance, control costs, and ensure it meets evolving business needs.

D is for Data-driven decision-making

Your infrastructure is too critical to manage based on guesswork and too complex to rely on expertise alone. Data analytics and machine-learning tools are essential for identifying trends, patterns, and anomalies in performance data so you can make better decisions about infrastructure optimization, capacity planning, and resource allocation.

E is for Ensuring security and compliance

If you are responsible for managing the performance of your infrastructure, protecting it from cyber threats and complying with industry standards and regulations are part of the package. You’ll need to implement security protocols, conduct regular security and compliance audits, and stay up to date with the latest security vulnerabilities and regulatory requirements.

F is for Fostering collaboration and communication

There are a lot of stakeholders involved in any enterprise infrastructure: IT staff, executive leadership, business owners, external vendors, the list goes on and on. Dashboards and reports must provide views into your infrastructure that reflect the specific information each stakeholder needs. Additionally, it’s important to establish clear communication channels and protocols to ensure stakeholders are informed about performance issues and progress toward performance targets.

G is for Gathering performance data

You can’t manage the performance of your infrastructure if you don’t have information about the performance of your infrastructure. You need to collect sufficient data from various sources, including servers, virtual machines, storage, networks, applications, operating systems, and other infrastructure components. Both breadth and depth of data are critical to monitor your hybrid cloud infrastructure’s performance, utilization, capacity, and health.

H is for Harnessing the power of automation

Automation is a powerful tool in infrastructure performance management. By automating routine tasks, such as system checks and updates, you can save time and reduce the risk of human error. Automation can also help you identify and remediate performance issues quickly, improving the overall efficiency of your IT operations.

I is for Implementing best practices

Your hybrid cloud infrastructure is too complex and too important to build performance management expertise as you go. Implementing industry-standard guidelines and IT operations best practices for performance monitoring, incident management, and change management help ensure your hybrid cloud infrastructure is optimized for performance and reliability.

J is for Justifying performance investments

Maintaining an infrastructure that meets business requirements and performs to expectations requires resources and budget—and it can be expensive. You need to be able to make a business case that outlines the benefits of proposed investments, and perhaps even the likely consequences of not investing. Successful justification requires you to provide credible data and analysis based on your current infrastructure and the anticipated future state.

K is for Keeping pace with emerging technologies

Right now, artificial intelligence and machine learning are quickly emerging as highly effective tools to transform IPM capabilities. Companies adopting AIOps and leveraging AI/ML for performance management, troubleshooting, capacity planning, and other critical functions can fully optimize their infrastructures and gain a competitive advantage. And who knows what may be on the horizon? Staying current with the latest trends and best practices and embracing emerging technologies will keep you at the forefront.

L is for Leveraging vendor partnerships

Your infrastructure uses a lot of hardware, software, networking, storage, and other components, which means you have a lot of vendors—and potential access to their domain expertise. Working closely with your vendors can provide valuable insights into the operation and performance of individual products.

M is for Monitoring performance metrics

You need to track KPIs such as CPU usage, memory usage, network bandwidth, and other critical factors to understand how your infrastructure is performing and identify potential issues, ideally before they have a discernable impact. With the right monitoring tools, you can automate this process and configure alerts when KPIs fall outside of acceptable ranges.

N is for Navigating hybrid/multi-cloud environments

Most enterprise infrastructures consist of on-premises, private cloud, and multiple public cloud environments. You need to understand how to optimize performance within each environment and how its unique characteristics affect the overall performance of your infrastructure. This includes selecting the right environment for each application or workload, understanding the performance metrics, and using the best tools and services to monitor and manage performance.

O is for Optimizing application performance

Application optimization—which includes identifying and remediating performance bottlenecks, optimizing code and configurations, and leveraging performance testing and tuning tools—offers two benefits. You can optimize to boost performance, increasing user satisfaction and business outcomes. You can also optimize to maintain existing performance levels at a lower cost. And sometimes, you can even accomplish both at the same time.

P is for Proactively managing incidents

The worst way to find out about a problem within your infrastructure is to get a call from a user. It’s far better to identify potential issues before they become significant problems. By monitoring performance in real time and flagging trends that could lead to slowdowns and outages, you can reduce downtime and the associated costs and improve infrastructure performance and reliability.

Q is for Querying dependencies

Examining the relationships and interdependencies between the various components and systems in your hybrid cloud infrastructure provides insights into how changes or issues in one can affect the performance of others. This helps identify potential risks or bottlenecks and facilitates proactive measures to mitigate any adverse effects on overall performance.

R is for Reducing mean time to resolution (MTTR)

Reducing MTTR—the time it takes to resolve incidents and return the infrastructure to normal operation—is critical for minimizing downtime and its impact on users and the business. This requires you to establish response procedures, use tools to understand likely impacts and track root cause, and leverage AI to recommend fixes.

S is for Scaling infrastructure for growth

As your business grows, your infrastructure needs to handle increased demand and workloads without affecting performance and reliability. Supporting this growth requires insights about past performance trends, predictive analytics to anticipate future demand, and recommendations for scalable options to meet those needs.

T is for Tuning workloads

A key component of infrastructure optimization is workload tuning. This involves adjusting resource allocation and settings—CPU or memory allocations, storage configurations, network parameters, etc.—to match the specific requirements of each workload for improved performance and efficiency.

U is for Un-silo-ing the troubleshooting process

Because your infrastructure includes so many components—network, compute, storage, etc., not to mention all of the individual hardware and software components—many different teams and vendors are involved. When something goes wrong, this can result in time-wasting finger-pointing. With data-driven troubleshooting and AI-based resolution recommendations, you can avoid turf wars and focus everyone involved on getting the infrastructure back to normal as quickly as possible.

V is for Validating configurations

You want to ensure that the settings and parameters of various components and systems are configured for optimal performance. Ongoing monitoring and alerting will let you know if performance drifts out of band. And with scenario planning and what-if analysis, you can make decisions about changes that will minimize future risks and keep systems operating at peak efficiency.

W is for Workload balancing

Keeping your infrastructure running at optimal resource utilization and performance levels requires you to distribute workloads evenly across systems to prevent any single component from becoming overloaded or overwhelmed. Workload balancing strategies, which may include dynamic workload allocation, load balancing algorithms, and intelligent resource management techniques, can help you avoid bottlenecks, maximize system capacity, and enhance overall efficiency.

X is for eXploiting AI-powered recommendations

With recommendation engines powered by artificial intelligence, you benefit not just from your own infrastructure data but from analytics that incorporate experience gained from working with other enterprises. Recommendations can provide valuable suggestions for many areas of infrastructure management, including resource allocation, workload balancing, predictive maintenance, infrastructure scaling, problem identification and resolution, and more.

Y is for Yielding comprehensive global visibility

When you break down the many data silos—multi-vendor computing, networking, storage, cloud, VMs, containers, databases, and more—you can open up visibility throughout your entire infrastructure. This is critical for unified observability across all of your private and public cloud environments.

Z is for Zooming in on data

Breadth of infrastructure data is critical—but so is depth. Systems that lack granularity, for example, because they use sampling or averages, can deliver “insights” that are misleading and can steer you to make suboptimal decisions that ultimately result in inefficiencies.

Keeping your hybrid cloud infrastructure running at peak performance

Your hybrid cloud infrastructure must meet the business’s functionality, performance and availability, security and compliance, and cost requirements. Managing all of this complexity requires sophisticated technology and deep expertise. Virtana can help. Virtana Platform is a highly modular, scalable multi-cloud insights platform that offers Infrastructure Performance Management, Capacity Planning, Cloud Cost Management, and Workload Placement to manage your entire hybrid cloud infrastructure more effectively. Try Virtana Platform for free

The post Infrastructure is Fundamental: Learn Your Hybrid Cloud ABCs appeared first on Virtana.

Capacity planning is hard

The vast majority of respondents—87%—are getting capacity planning wrong. While 21% tend to underprovision and 28% err on the side of overprovisioning, a larger number (38%) are both over- and underprovisioning on a regular basis.

One critical occasion for capacity planning is when you’re moving workloads from one environment to another. The capacity calculus changes depending on the particular environment, and most organizations, 98% of them, are doing a lot of migrations. Almost two-thirds (62%) are planning to migrate workloads from the public cloud to private cloud/on premises, and nearly the same number (59%) will be migrating new workloads to the public cloud. Given organizations’ track record, chances are high that capacity for these migrations will miss the mark. 

Data for informed capacity planning is lacking

We asked about top hybrid/multi-cloud infrastructure management challenges, four of which are critical for effective capacity planning, and all showed up in the top five. Almost half of the respondents (47%) struggle with getting a global view of utilization and spend across their entire infrastructure. Without that global view, you’re likely making siloed capacity decisions that may not allow you to be fully rightsized and cost-optimized. And in fact, 40% said that they are hard-pressed to say optimized and rightsized on an ongoing basis. Around one-third of respondents (35%) have difficulty mapping utilization and spending back to business entities, which can make it hard to factor business prioritization and risk into capacity decisions. And one-third (33%) say making appropriate workload placement decisions is challenging.

When asked to identify their top challenge from the list, respondents put getting a global view of utilization in second place (20%) and staying optimized/rightsized on an ongoing basis in third (17%).

Make capacity planning data-driven—and ultimately more accurate—with Virtana Capacity Planning

With Virtana Capacity Planning, part of the Virtana Platform, you can forecast infrastructure demands across your global hybrid infrastructure. Scenario-based capacity projections allow you to anticipate business needs, and AI-powered cloud budget forecasting helps you identify trends and forecast future growth. Virtana Capacity Planning enables you to:

• Forecast future demand based on usage patterns and risk exposure
• Anticipate business requirements based on planned growth or changes
• Identify potential availability issues before they occur

Get the survey report: The State of Multi-Cloud Management

The post Cloud Capacity Planning Is a Hit-or-Miss Exercise That Mostly Misses appeared first on Virtana.

The Dell and Virtana relationship runs deep, going way back to when both companies had different names. Rewinding back to 2006 when I was a project manager at EMC, if we needed to do deep troubleshooting analysis on block storage solutions (Clariion and Symmetrix/DMX at the time), we would call in a Finisar Probe. The Finisar Analyzer was a 2U appliance with four ports capable of analyzing 1GB and 2GB fibre channel traffic, and it had to sit inline with a customer’s production data path. It was clunky, but it was effective for solving the most complex support issues.

I just found this guy on eBay for $30:

Jumping ahead a bit to 2008, some of the Finisar IP was spun out to found Virtual Instruments. The solution paired with passive traffic access points, which meant the device no longer needed to sit directly in the data path, making it a bit more elegant. There was also a new UI: NetWisdom. EMC customers were now leveraging Virtual Instruments’ ProbeFC not only to reactively solve complex VNX and VMAX infrastructure challenges, but also to proactively monitor performance in complex SAN environments.

Then came the explosion of virtualization technology, which only increased the complexity of these environments. This was a likely driver for EMC to partner closely with and ultimately acquire VMware. It was also the catalyst for Virtual Instruments to start development on agentless, software-based data collection, with ProbeVM for vCenter being the inaugural integration for VirtualWisdom (now Virtana Infrastructure Performance Management).   

Fast-forward to the era of hyperconverged and cloud compute. In 2016, in a strong signal of ever-converging infrastructure, Dell acquired EMC. This was also around the time that Virtual Instruments merged with Load Dynamix, a workload generation company, and acquired Metricly, a cloud optimization startup, and became Virtana. This only deepened the relationship, as Dell/EMC was, and continues to be a customer of the Load Dynamix (now Storage Load Testing) product line to test hardware products and code releases for stability and scale before releasing to the public. This enabled connections at the product and engineering levels that have aided Virtana development efforts toward software-based integrations with the Dell/EMC storage portfolio. 

And here we are today. Dell is currently the largest (by a lot) reseller of Virtana products. We programmatically help their technical support organization, deploying a virtual edition of VirtualWisdom as part of Dell’s level 3 support cases. Dell and Virtana products are leveraged together, with many of Dell’s top accounts depending on both companies’ technologies to run their businesses.

Virtana and Dell are Better Together—and Here’s Why

As Dell customers seek cutting-edge technology to power their mission-critical applications, they also need an intelligent way to contextualize, monitor, and manage those workloads. Virtana’s high-fidelity and application-centric monitoring, cross domain-visibility, and workload intelligence complement the entire portfolio of industry-leading Dell solutions.

Cross-Domain Visibility

Virtana’s network, compute, hypervisor, and container integrations expand insight beyond the storage layer to provide a unified view of performance across tooling that’s traditionally siloed. This enables alignment of cross-functional teams through a common set of data points and capabilities. It provides a topology view that contextualizes the complete data path from application to storage volume.

Application-Centric Monitoring

With Virtana, you can guarantee continuous availability and performance against SLO/SLA for mission-critical applications. Virtana automatically maps infrastructure components to the applications that are consuming its resources, adding business-level context to high-fidelity data. This enables you to understand application and infrastructure interdependencies as the foundation for digital transformation initiatives.

Advanced Analytics

High-fidelity data collection and persistence facilitate highly accurate results and recommendations from our AI/ML-based analytics engine. With Virtana’s advanced analytics you can be alerted to observed deviations in workload behavior and leverage runbook-style investigations with remediation steps that can trigger autonomous action through bi-directional integration with Service Now. You can constantly ensure that your workloads are balanced and optimized, and consistently predict infrastructure bottlenecks and time to compute, network or storage resource exhaustion.

Workload Intelligence

Virtana delivers granular performance metrics for intelligent workload placement. Workload profiling enables data-driven digital transformation decisions, enabling you to “know before you go” for successful technology refresh in the private cloud and to determine which workloads are best fit for hybrid cloud solutions like APEX. You can see how applications will perform in their destination state, and what will they cost compared to on-premises deployment. And you can improve capacity forecasting with highly accurate predictions of future resource consumption across compute, network, and storage.

Rich Dashboards

VirtualWisdom’s comprehensive understanding of the data supply chain provides the basis for rich dashboards that deliver service assurance, visibility, and control to administrators, architects, and executives.

Ease of Deployment

It’s never been easier to deploy Virtana and Dell technologies together. VirtualWisdom has evolved into a modern, distributed microservices-based architecture that can be deployed on VMware. You can now even leverage the AppsON capability of PowerStore’s internal vCenter to deploy infrastructure-wide monitoring directly on the array. And, while you can still leverage our flagship performance probes for up to 32G FC traffic, we now have agentless, software-based integration with coverage across:

• All major Dell storage offerings: PowerMax, PowerStore, PowerScale, PowerFlex, VxRail, XtremIO, Unity, and VPLEX (coming soon)
• Connectrix switching: Brocade (Including SANnav) and Cisco (including Nexus and telemetry streaming from MDS),
• Compute: operating system (Linux, Windows, Solaris), hypervisor (ESX, Hyper-V, KVM), Kubernetes, Cisco UCS

Technology-Specific Integrations

Block and File Storage Solutions

PowerMax

PowerMax is a fitting solution to power the most mission-critical workloads that can’t afford any downtime or compliance issues. Paired with our software-based integration for PowerMax (formerly VMAX), VirtualWisdom can ensure continuous availability and performance at any scale. You can:

• Guarantee end-to-end performance and avoid upstream infrastructure bottlenecks while leveraging the fastest storage media and protocols (NVMe, flash, or storage class memory)
• Add business-level context by automatically grouping related infrastructure components and high-fidelity metrics into applications
• Ensure business continuity by monitoring replication functions like SRDF and SnapVX
• Use predictive capacity forecasting to track your infrastructure’s efficiency, and alert you to potential future resource exhaustion and bottlenecks
• Pair with industry-leading wire data collection and switch telemetry for deep protocol analysis of every transaction at massive scale

PowerStore

According to Dell.com, “the groundbreaking PowerStore family of all-flash data storage appliances transforms traditional and modern workloads with a data-centric, intelligent, and adaptable infrastructure that delivers revolutionary new capabilities such as AppsON.” With the VirtualWisdom integrations for PowerStore, you can fully realize the value of these industry-leading innovations. You can provide business-level context to applications that are hosted on external compute, as well as those leveraging the “AppsON” embedded vCenter. Paired with our Kubernetes integration, Virtana helps guarantee performance of PowerStore’s container storage module (CSM) for file- and container-based workloads at block storage speeds. Combined with our hypervisor integration for vCenter, Virtana provides unified observability for storage provisioned as vVols and other VMware functions like VAAI and VASA. You can leverage Virtana’s workload intelligence and analytics engine to validate and augment PowerStore autonomous operations, including automated data placement, resource balancing, dynamic node affinity, and assisted migration. And, you can pair with Virtana’s legacy Dell/EMC storage integrations, like Unity and XtremIO, to effectively plan, monitor, and benchmark application performance before, during, and after migration to PowerStore.

PowerScale: Any Data, Anywhere

PowerScale supports a wide range of data types and diverse workloads. Combined with our software-based integration for PowerScale (formerly Isilon), VirtualWisdom provides full-stack end-to-end visibility of PowerScale clusters, protocol flows, and the applications and servers consuming those resources. This enables you to:

• Assure the performance, availability, and efficiency of workloads on PowerScale clusters regardless of protocol (NAS [NFS, SMB], big data [HDFS], S3, HTTP, or FTP)
• Gain comprehensive visibility and unparalleled correlation for easy identification and root cause analysis, even for the most challenging issues
• Validate policy-based workload placement and resource tiering
• Ensure the storage efficiency of OneFS, and proactively identify upcoming resource constraints  

Unity / Unity XT

Unity XT storage arrays are designed for performance, optimized for efficiency, and built to handle multi-protocol and hybrid-cloud workloads. These hallmarks all align directly with Virtana’s key competencies:

• Provide application context for workloads running on Unity infrastructure
• Combine with OS, vCenter, and Kubernetes integrations for full compute to back-end storage visibility regardless of storage pool resource type (block LUNs, file systems, or vVols)
• Enable predictive capacity forecasting to project time to required expansion or refresh
• Enable data-driven decisions on best technology refresh and workload placement options based on granular insights from VirtualWisdom
• Guarantee seamless technology refresh before, during, and after migration, combined with our PowerStore or other storage integrations for the destination array

XtremIO

Enterprise customers have historically deployed some of their most resource-intensive applications on XtremIO storage. Combining XMS-level data from Gen1 and Gen2 XtremIO systems with the cross-domain visibility of the Virtana Platform helps ensure availability and performance of these applications in their current state, and also helps plan for their future. You can combine real-time and historical capacity usage, performance, and health information from the physical and logical components of the X-brick architecture with additional metrics from related interconnected infrastructure. You can gain visibility into which XtremIO resources an application is consuming, as well as gather latency metrics at the host, volume, and application levels, and understand how these relate to tracking against application SLO/SLAs. And you can enable seamless technology refresh by providing unique insights into the workloads that currently reside on XtremIO:

• Before: Data-driven decisions on workload placement pre-technology refresh
• During: Combine with PowerStore, PowerMax, or other storage integration to monitor during migration
• After: Benchmark performance vs. legacy systems

VPLEX

Dell/EMC VPLEX creates a flexible storage architecture that enables data portability and helps maximize asset utilization across active-active data centers. Today, VPLEX customers can leverage VirtualWisdom’s wire-data collection with a hardware monitoring device to definitively pinpoint error conditions and latency within a VPLEX environment. Virtana is currently developing a software-based integration for VPLEX (for release in 2H 2022) to include visibility beyond the abstraction layer of storage virtualization to automatically map application workloads from compute through network to back-end storage.

Software-Defined Storage Solutions

PowerFlex

PowerFlex delivers extreme flexibility, massive performance, and linear scalability as the foundation for organizations to modernize their data center and workload infrastructure. VirtualWisdom provides full-stack visibility across the applications and servers consuming and mounting PowerFlex resources, clusters, and storage pools, and the network flows between clients and resources. It enables you to:

• Gain real-time and historical performance visibility from the PowerFlex system, client (SDC), storage (SDS), volumes, storage pools, and protection domains
• Dynamically map and create logical equivalency between resources discovered by our vCenter integration (like ESX datastores) and PowerFlex entities (like volumes)
• Auto-detect excessive evictions and identify resource hogs and noisy neighbor problems
• Know when a rebuilding/rebalancing process impacts performance
• Pinpoint large file and storage pool filling issues

VxRail

VxRail delivers converged infrastructure, founded on VMware vSAN. You can combine the flexibility of this HCI solution with the performance assurance provided by VirtualWisdom’s vSAN and Kubernetes integrations to create an ideal platform for innovation across core, edge, and cloud: 

• Understand how applications stress converged and hyperconverged infrastructure
• Visualize converged infrastructure topologies from client to storage to device
• Get real-time and historical performance visibility from application to storage
• Continuously monitor CI and HCI environments for capacity issues across compute, network, and storage
• Identify and resolve high write cache evictions, rebuild/rebalance activities, noisy neighbors, and more
• Combine with VirtualWisdom integration or Kubernetes for enhanced visibility into container workloads running on HCI

VxBlock

VxBlock integrates powerful Dell storage and data protection into a turnkey converged system supporting all your high-value, mission-critical workloads—from the core data center to the cloud. VirtualWisdom is certified to deploy directly within VxBlock, and Virtana has software-based integrations for every layer of the VxBlock architecture to completely unite performance monitoring for this converged solution, regardless of the storage, networking or compute configuration options chosen:

• Storage integrations: PowerStore, Unity, PowerMax, XtremIO, and PowerScale
• Networking integrations: Cisco Nexus and Cisco MDS, including telemetry streaming
• Compute integrations: Cisco UCS, vCenter, OS, and Kubernetes layers

Switching Infrastructure (Connectrix)

The Dell Connectrix family of directors and switches moves your organization’s vital business information to where it’s needed quickly and securely, with the highest performance, the highest availability, and unsurpassed reliability. Combine it with Virtana’s software-based switch integrations, which gather data via SNMP/SMI-S or OS-API based sources, to:

• Dynamically map applications to storage resources such as fabrics, switches, vLANs, ISLs, switch ports, and storage array ports
• Gain context into application dependencies and behavior via NetFlow, sFlow, and JFlow data ingestion from PowerSwitch devices
• Automatically identify and resolve slow drain conditions and application workload changes using analytics-driven runbooks
• Trend, forecast, predict, and alert on capacity usage across network resources (ports, switches)
• Create topology-based views in application context with health and utilization metrics from Cisco MDS, Cisco Nexus, and Brocade
• Stream high-fidelity telemetry performance metrics from the Cisco MDS line of switches (Cisco Nexus and Brocade via Apache Kafka Stream from SANnav coming in 2H 2022)

PowerEdge and Host Monitoring

Combine the reliability and performance of the Dell PowerEdge line of servers with Virtana’s OS, hypervisor and container-level integrations for true visibility into the compute layer that powers mission-critical applications. You can:

• Automatically map applications and service tiers to hybrid compute infrastructure
• Trend, forecast, predict, and alert on capacity usage across all compute resources (CPU, memory, network, disk)
• Optimize placement of compute workloads across your virtualization estate to improve performance and eliminate migration churn
• Rightsize application components based on usage and business value, and apply changes within your change governance policies
• Leverage VirtualWisdom integration with UCS Manager to eliminate the challenges associated with abstraction layers introduced by Cisco Unified Compute
• Visualize Kubernetes workloads and their relationships to underlying infrastructure (VMs, physical hosts, networking, and storage)

An Empowering Combination

Virtana delivers unprecedented visibility and actionable insights into the performance, health, and utilization of hybrid IT infrastructure, while Dell/EMC’s storage solutions deliver enterprise-class performance and scale. Together, Virtana and Dell empower you to:

1. Cost-effectively ensure the performance and availability of mission-critical applications
2. Proactively prevent infrastructure-related slowdowns and outages
3. Enable business agility and digital transformation across private, public, and hybrid clouds

Contact us if you’d like to learn more.

The post Aligning Dell’s Industry-Leading Storage and Data Infrastructure Portfolio With a Comprehensive Monitoring and Optimization Platform appeared first on Virtana.

According to the results of our recent State of Hybrid Cloud and FinOps study, only 18% of cloud decision makers surveyed said that they have been able to avoid unnecessary cloud costs. This does not bode well for IT teams responsible for managing hybrid cloud infrastructure within a budget that we CFOs care so much about (i.e., everyone). Where are those excessive costs coming from?

• 41% experienced workloads bursting above agreed capacity
• 35% overprovisioned their compute or storage resources
• 34% over-bought or had unused reserved instances
• 34% stated they had storage blocks no longer attached to a compute instance
• 22% were vexed with poor job scheduling

Half of the respondents reported experiencing two or more of these problems, and 26% were plagued by three or more. Furthermore, given the relative lack of visibility organizations have into their hybrid cloud infrastructures, these numbers are likely understated. Let’s examine each of these budget-busters in turn.

1. Workloads bursting above agreed capacity

Cloud bursting, which is when a workload running on premises or in a private cloud moves or “bursts” into the public cloud when demand spikes, can prevent overload. If you don’t have a good handle on what’s happening with your workloads and how they’re evolving, bursting and the associated costs can escalate well beyond what you’ve budgeted for.

2. Overprovisioning of compute or storage resources

Overprovisioning to support future growth is an age-old approach IT infrastructure teams use on premises. Any costs for capacity you may not be currently using aren’t wasted; these are capex investments that don’t change the amount you pay over the life of those assets. In the cloud, however, because you don’t need to invest in hardware, overprovisioning isn’t necessary, assuming you have an elastic environment. Sometimes it is used to mitigate risk—to ensure that workloads don’t end up under-resourced. The difference is that these “extra” costs are opex that could be eliminated or at least minimized.

3. Over-buying and/or under-utilizing reserved instances

You can save money on your cloud deployment by committing to a particular plan—called a reservation, reserved instance, or programmatic discount—that delivers discounts on the resources you use. While you might have some flexibility to modify or exchange a reserved instance, you typically can’t cancel it, so if you over-commit, the savings might not materialize.

4. Unattached storage blocks

There are a couple of reasons you might have storage blocks that aren’t attached to an active instance. You may need to keep it for audit and compliance purposes, for example. Too often, however, instances get terminated but the attached storage does not—and you continue to pay for that orphaned volume. You need a way to track, report, and eliminate these wasteful, unused resources.

5. Poor job scheduling

If you don’t schedule batch processes or big jobs well, you could end up degrading the performance of other applications. It’s not just a matter of adding capacity. More capacity will always solve the problem, but it might also cost you more than necessary. Instead, you could do things like co-locate a workload that needs to be run at night with another workload that only runs during business hours.

Keeping your cloud costs in check with Virtana Optimize

So, how do we CFOs help our IT/DevOps/Cloud teams keep these cloud costs from spiraling out of control? With Virtana Optimize, you can optimize your cloud capacity and costs on an ongoing basis, so you can stay on budget, even as conditions and options change, and avoid an end-of-month billing surprise. With Optimize you can:

1. Improve forecasting and planning. Use real-time data collection and analytics for ongoing cost management and resource optimization recommendations to meet SLAs and stay on budget.
2. Understand cost-impacting changes in real time. Automatically optimize Amazon EC2 and Azure VM instances with rightsizing recommendations. Quickly adjust to changes in cloud service provider offerings to optimize cost structures.
3. Manage risk more cost-effectively. Tune sizing based on your organization’s risk tolerance with “what if” analysis that includes CPU, memory, I/O, and ingress and egress charges. Safely adjust over-allocated resources to save on your bill without risking production.
4. Optimize reservation planning. Avoid long-term programmatic discount commitment mistakes by finding the ideal resource settings before purchase. Track the amortized value of programmatic discount usage at the instance level.
5. Identify orphaned or unused resources. Automatically identify unused compute instances, storage on stopped instances, and unattached storage blocks. Quickly spot wasted spend with proactively emailed reports.

We need all the help we can get managing our costs in this increasingly complex IT landscape. Fortunately, there are amazing resources available, including our own Virtana Optimize. We have seen our customers truly surprised at the savings they see. The cloud is an amazing resource; now you can keep the costs in check, mitigate surprises, and lower that hosting bill. Amazon may not thank you, but your shareholders will. Request a free trial today!

Get the survey report: State of Hybrid Cloud and FinOps survey

Request a trial: Virtana Optimize

The post 5 Ways Cloud Costs Can Spiral Out of Control appeared first on Virtana.

An application is a set of functions that serve a business purpose. A workload is the stress placed on the infrastructure by that application. For example, when a customer calls a company’s support line, their account information is on the screen when they’re connected to a support representative. To make this happen, the customer support application runs in the background to look up the incoming phone number, collect and present the associated account details, and display that information on the representative’s screen. The whole process touches code that runs on operating system(s), which sit on virtual machines (or bare-metal servers), which rely on storage subsystems and networking subsystems to communicate. The effort needed to support this application—CPU, memory, network, and disk consumption—is what I consider a workload.

Each application has a workload fingerprint. When the application was initially built, the developers generally knew how much horsepower was needed to make it work. For instance, they knew the application in our example had to support 500 customer service reps who average one phone call every 2 ½ minutes. They can determine how many queries will be executed on the database, how many rows will be returned, how much disk will be accessed, how much CPU is consumed to crunch the numbers, etc., and spec out the infrastructure needed to support the application. Pre-production testing can aid in obtaining a more accurate workload fingerprint; rather than guessing at consumption values, a developer can run tests that will simulate production. 

Workload placement considerations

When most people think about workload placement, they are looking for the optimal place to run that workload.  Some companies are only mature enough to find space available while others are looking for the most efficient place to run the workload, efficiency being a code word for “cost effective.” (If your thoughts jumped to “run slow apps on slow disk,” you get my point.) However, you need to consider more than just cost.

For example, cost will be less of an issue for a mission-critical workload that absolutely has to be lightning fast. In that case, you should optimize on performance. Some workloads don’t have to be fast but they do have to be always up, so those should be optimized on availability or redundancy. You need to understand the critical dimensions and then stack rank your workloads accordingly. There are three dimensions you could optimize toward: cost, performance, and availability. Each has its own implications when it comes to placement decisions.

Evaluating placement opportunities

Once you’ve characterized what an optimized application means (and each app is different!), you need to look at what’s available in your infrastructure. The key word here is available. It’s not enough to just look at what’s currently free—that’s a myopic way of viewing your infrastructure. Workloads are granted rights to resources that they may or may not be consuming at the present moment. 

Imagine a scenario where a hyper-critical application’s workload is busy from 6 am to 6 pm, Monday through Friday. You have placed it on expensive hardware. But for 12 hours each weekday, and 24 hours over the weekend, that expensive gear sits relatively idle. If a critical batch-processing workload appears, you must consider co-locating those two workloads together. What this means is that at any given moment, all of your options are on the table, and you need to consider the broadest set of permutations to truly optimize your infrastructure.

This is not a one-time exercise

Conditions change over time. You need to understand your workload needs on an ongoing basis and see how you’re trending. When that customer support team grows to 750 reps, and process improvements drive down the call average to one every 2 minutes, there’s an impact to your infrastructure. The application hasn’t changed, but the workload has. This so-called workload drift could require you to adjust your infrastructure to keep performance at expected levels, and to avoid surprise costs if you’re running in a cloud environment. And yes, this means your infrastructure architect’s job is never truly finished, and they need a way to constantly probe for better ways to run the workloads they have.

Keeping workloads optimized

If this sounds like a lot of work, it is—which is why you need tools to automate the process. And that’s exactly what the Virtana Platform helps you do. Our Optimize module helps you characterize your workloads, evaluate your placement options, and recommend improvements based on your priorities—on premises and in your public clouds.

If you’re ready to #KnowBeforeYouGo, contact us to request a Virtana Platform demo.

Cloud Optimization and Rightsizing

The post Workload Placement Is Science, Not Art appeared first on Virtana.

Performance

Most cloud services do not give you a Service Level Agreement (SLA) for application performance. They will usually give an availability SLA, but being available and ensuring your application is performing well as customers use it are very different.

Capacity

Is your migration plan based on actual capacity used? Remember most VMs and allocated storage run at less than 60% capacity (less than 20% in a lot of cases) so you’re most likely paying for overprovisioning.

Dependencies

It’s rare for an application to only operate within its own infrastructure. It will share server space, switch nodes, and storage with other traffic. To migrate an application, it’s vital to know the topology and if it can be isolated. An application with multiple dependencies is not an ideal candidate to move so should either be kept in-house, migrated with another shared resource using applications, or re-coded to be independent.

The starting point is to benchmark the application performance, look at its actual capacity usage and its projected growth over time, and see if it’s suitable to move. A robust AIOps platform will provide the performance, topology of the infrastructure, and how the application is using it. It will also show under and overprovisioned VMs, server, and storage capacity.  Assuming performance and dependencies are good to go, you can concentrate on highs and lows of capacity usage.

Most non AIOps tools either don’t give an application view of capacity or advise on what needs to be increased if resource usage strays over into an abnormal state. This means either planning capacity without full knowledge of requirements or reacting to a situation as it arises which strains resources and can impact budgets.

Comprehensive AIOps platforms, like VirtualWisdom from Virtana, monitor the application usage of all infrastructure components in real time but also store transaction statistics so trends can be analyzed over weeks and months. This approach ensures capacity is there when needed and predicts future capacity growth so purchasing and planning is organized in a structured fashion with no unplanned reactive capacity upgrades.

Contact us to learn more or let’s set up a time to talk through your specific needs. More about Cloud Cost Management

The post Capturing and Containing Hidden Cloud Costs—How Overprovisioning Can Hurt Your Budget appeared first on Virtana.

No matter what’s driving your move to an AWS or Azure cloud, two things are true. One, you don’t want to under-provision, which could create performance and availability issues. And two, you don’t want to overpay, because no one ever wants to do that. One of the key decisions you must make is which Amazon EC2 or Microsoft Azure virtual machine instance configuration you need. It’s a scoping exercise, but several factors make this easier said than done. There are six common barriers that can prevent companies from accurately scoping their cloud VM requirements, forcing them to rely on guesswork and increasing the chances they’ll under-provision or overpay. 

1. The choice is overwhelming. 

Having options is good, and so is configurability—these enable you to better tailor deployment to your needs. But when the total possible permutations number in the hundreds of thousands, you have too much choice. This can be paralyzing especially as new types, sizes, and generations are introduced by cloud providers every couple of weeks. You need to be able to automate the analysis of all those combinations so you can easily find the ones that will truly best suit your needs.  

2. A CPU-centric focus provides an incomplete picture. 

There is guidance available to help you navigate the range of options, but it often focuses primarily on CPU utilization. That’s certainly important, but it’s by no means the only factor you must consider. If you don’t take other critical computing dimensions—such as memory usage, IOPS, and network bandwidth—into account, you may create a bottleneck in capacity, causing a slowdown in your application performance. 

3. Average and max data are misleading. 

When considering what you need to size your VM to, there are several approaches. One is to use averages. This might be sufficient if there’s very little variability in your workloads, but that’s often not the case. The more variable demand is, the less representative the average number is for your environment and you risk under-provisioning your VM. Another approach is to use max, or peak, data. This is the “safest” approach from a capacity planning perspective, but if your peak is very short-lived—for example, a few minutes at midnight during the week due to backups—you could end up over-provisioning. You need to consider other statistical aggregation methods, such as 95-percentile, to be safe without resulting in waste. 

4. Cost reduction must to be weighed against risk.

Because there are so many options available at different price points, it can sometimes seem as if the final decision comes down to cost. This might be true if we lived in world of certainty and predictability, but, of course, we don’t. Instead, you need to evaluate cost and risk. If one option is cheaper by several hundred dollars but has, at a certain threshold, a much higher risk of performance bottlenecks or even downtime what would cost the organization thousands, do you still go with the lower-cost choice? Maybe. It depends on your company’s individual risk profile. The point is, you should make the decision deliberately and by calculating risk tolerance mathematically.

5. You need to plan for the future. 

Your company wants to grow and evolve—every business does—and your infrastructure must keep up, and not solely based on historic usage. It’s not easy to plan ahead. This is especially in a climate of transformational and fast changes, or if you are provisioning an environment ahead of your application launch, which may be part of the reason you migrated to the cloud in the first place. You need to understand how much headroom each option provides, based on your expected workloads and risk tolerance, which requires the capability to conduct what-if analysis. 

6. You need to account for existing commitments and requirements.

There may be certain conditions you want to take into account. For example, if you’ve already pre-paid or otherwise committed to a particular EC2 or VM type (Reserved Instance), you need to take full advantage of it for the length of the term. Or if there are certain types of VMs you know won’t work or you otherwise don’t want to use, for example, if you need to avoid burstable CPU credit, or want to stick exclusively with Intel chips (vs. AMD). You may also have varying requirements across different applications, regions, etc., where workloads may require different thresholds than others. You need to factor all of these considerations into your analysis. 

AWS and Azure VM Optimization With CloudWisdom

Virtana’s CloudWisdom cloud management platform includes an automated recommendation tool to help companies right-size their AWS and Azure VMs. It combines granular measurement and aggregation of resource utilization with knowledge of the thousands of ever-expanding configurations for AWS and Azure resources to identify opportunities to optimize. It looks at all the critical dimensions, including CPU, memory, IOPS, and network bandwidth based on usage over time. It allows you to set constraints, including or excluding factors to reflect your specific requirements, so you can find the ideal resource settings before making long-term reservation commitments. And it allows you to perform what-if analyses to help you scale resources to match growth. Contact us to learn more.

More about AWS and Azure Clouds

The post 6 Common Mistakes in AWS EC2 and Azure Cloud VM Optimization appeared first on Virtana.

1 – How we got here

When mission-critical applications were all implemented within your data center, capacity management seemed easy – Most organizations deployed infrastructure sets (compute, network, and storage) to meet their 95 to 99% capacity requirement. For a retailer, that might mean planning around a “Black Friday” date (Cyber-Monday wasn’t around then). For a bank or a manufacturer using ERP or financial systems, this might instead be the end of year close. I’m sure you can think of a date for your own organization’s highwater mark for resource requirements. The results of this approach were massive overcapacity and high expense levels – but it worked “back in the day.”

Keep in mind that this was when loadings were lower, mobile wasn’t on the scene, and at first, these were physical only systems.

Next up was virtualized infrastructure, overwhelmingly on VMware for the compute layer, with separate dedicated physical servers and enterprise storage environments to support transaction processing needs. Network devices started to support application metering to ensure that mission-critical applications had the bandwidth they needed to meet SLAs in that same worst-case (Black Friday) scenario. This model allowed for more flexibility, with the option of expanding infrastructure within the limits of on-premises or hosted environments – still within the bounds of ‘owned’ infrastructure but allowing for better cost-efficiency. Capacity management here often meant that you had enough spare compute, network, and storage that you could repurpose to meet a relatively predictable top-end load.

When the cloud came on the scene, we often called these virtualized environments “private clouds.” 

2 – Where we are today

Now, we’re well past the initial adoption era for cloud – and the vast majority of mission-critical applications are hybrid, with a mix of public cloud and backend data center or hosted resources. Data centers disproportionally have critical storage environments or legacy backend systems to enable organizations to maximize control of storage access speeds and transactions. In many cases, application infrastructure has spread to wherever an organization’s journey through digital transformation has taken them.

• Single virtualization environments have morphed to multiple environments with two or more hypervisors.
• Compute resources have a presence on-site, but the vast majority now also include a permanent component in single or multiple vendor public cloud environments to allow scaling of that layer as needed.
• Networks now have multiple implementations – physical and software-defined on-premises and software-defined implementations in cloud environments.

But that’s not all that’s changed. Add in the exponential increase in demand for access to services, and it’s a new world of clients that can consume mission-critical application resources:

• Traditional PCs in the hundreds of millions
• Billions of mobile devices across the globe
• A tsunami of IoT devices that have only starting to build

Storage needs are also growing massively, even as the demand for responsive user experiences increases. And peaks are no longer just the “Black Friday” scenario – peak scaling is still periodic, but with less predictable, more frequent peak loads. Intelligent workload optimization and scaling within internal private clouds have become critical, enabling the right local resources can be available at the right time. What’s more, with public cloud-based infrastructure (even public cloud systems deployed in your data center), cost now enters the picture more than ever with highly variable costs that can be hard to predict for cloud infrastructure. Physical backend storage and systems must balance with highly scalable cloud resource sets – and decisions about reserved capacity, scaling, instance types, locations, and networking are critical to ensure uptime and meet SLAs.

3 – What do these changes mean for capacity management?

What do all of these changes mean for capacity management? If you are supporting one of these mission-critical applications, it’s a sea change for applications views, monitoring, and management for capacity:

• Context – application and location-centric views of infrastructure: Application-centric topologies are required, combined with detailed relationship data about infrastructure elements, their locations, capacities, and status. Context has to include both the application, detailed cloud/virtual/physical environments and any other uses of resources upon which the application is dependent.
• Continuous discovery of applications and infrastructure – with capacity analysis and thresholds automatically applied: With auto-scaling now available with compute, network, and storage layers, continuous discovery can’t be optional. What’s needed is continuous application level and infrastructure element discovery – with best-practices capacity rules (or your organization’s equivalent) across the local and cloud environments underlying your hybrid application.
• Siloed tools won’t do: The tools from any single infrastructure element offering, or cloud vendor’s environment are insufficient for the task. Siloed solutions that cover limited infrastructure elements can’t tell you enough to prevent unplanned downtime and keep performance SLAs.
• Balancing performance, availability, and cost are more important than ever: Having a mission-critical application doesn’t mean that you have a Manhattan Project budget for managing it. Good decisions are required about the allocation of limited resources on-site and minimizing the costs of bursting and scaling to cloud resource sets. The alternative is more over-provisioning and overcapacity combined with large and unpredictable cloud service bills.
• Long-term data sets with granular data: Tools that capture only snapshots of short data baselines for hours, days, or even weeks aren’t enough. Long term data is required. And that data needs to be at the most granular level available – collecting data from infrastructure elements and minimizing the losses of insight caused by averaging data points. Some problems can’t be avoided (or found when they occur) without the most detailed sets of long-term data.
• AIOps – Powered by AI, machine learning, and statistical modeling and algorithmic correlation tools in addition to traditional trending and baselining: And making sense of all this data, all of these environments, and all of these capabilities requires intelligence that isn’t available from yesterday’s tools. Given the complexity of managing even the more straightforward mission-critical applications of the past, working within today’s highly-scalable, highly variable environments requires intelligence that is applied to every aspect of capacity management from cost to resource allocation to availability and more.
• Full integration between application-level tools, infrastructure management, monitoring, ITSM (or DevOps) resources, and cloud environment tools: It’s not enough for even a high level of infrastructure capacity management to operate as a standalone tool – integration with application-level management tools like AppDynamics or DynaTrace along with ITSM resources such as ServiceNow (or DevOps operations) are hard requirements. And hybrid infrastructure management and monitoring without a view into the cloud resource stack, services, performance, and cost isn’t a solution that will work.

No one else puts the full picture for hybrid applications and infrastructure together like Virtana’s VirtualWisdom solution. If you’d like to learn more about Virtana solutions, consider one of our free trials – or take a quick look at Virtana today with this quick video from our CEO, Philippe Vincent.

More about Cloud Performance Monitoring and Management

The post Mission-critical Hybrid Capacity Management – It’s Time appeared first on Virtana.

As a healthcare CIO mandated with the transition to electronic healthcare records, you’ve done your due diligence, evaluated various EHR vendors and most likely settled on Epic, a software vendor with over 25% of the US acute care hospital market share.  You’ve followed Epic guidelines for minimum hardware requirements and acquired what you believe is the right workstation, server, networking, and storage infrastructure for Epic.  How do you take precautions to ensure that you don’t have outages due to underlying shared infrastructure – comparable to the 6 day outage reported at Boston Children’s Hospital in 2015?

There are many factors unrelated to Epic itself which could cause application performance issues, and even downtime:

If you are a large organization, Epic recommends that you have a tiered database architecture and this is based on InterSystems’ Enterprise Caché Protocol (ECP) technology.  Caché is a commercialized version of a 53-year old database called MUMPS (Massachusetts General Hospital Utility Multi-Programming System).  A unique characteristic of Caché is that it has an I/O access pattern of continuous, random database file reads interspersed every 80 seconds by a large burst of writes.  This puts a demand on the shared SAN-attached storage array that it should have enough cache available to absorb all 80 seconds of write into cache and de-stage it before the next write cycle from Caché hits the storage array.  If the storage array doesn’t have enough write cache available it will hold off acknowledging write requests till its own cache is free up.  If Epic Caché cannot finish its writes in 80 secs, database access could exhibit latency.  This could be due to no fault of Epic but a factor of the underlying shared hardware infrastructure.

Why can’t you just rely on the application performance monitoring tools provided by your vendor?  For the simple reason that arrays usually have tracing with 60 second summaries.  As you can imagine, a 60 second summary of an 80 second process isn’t terribly useful.  Virtana Infrastructure Performance Management has wire level visibility into Fibre channel (or NAS protocol) traffic – every single conversation at line rate – and offers second-by-second summaries which can make a world of difference.  In addition, 99.9th and 99.99th percentiles are shown by timing every single exchange on the wire and placing the timed result in histogram represented buckets, ranging from sub milliseconds upwards.

You may be thinking: But I’ve followed all the guidelines sent to me by Epic…  For instance, Epic might tell you “all average read latencies must be 12 msec or less for ECP configurations”.  However, your datacenter monitoring expert might turn around and ask you “Noted but at what granularity? Is it to be every 5 min, every 1 min or every 1 sec?”  Guidelines from a software vendor are good but the devil is in the detail in how customers interpret these guidelines.

You may well ask: Why can’t I just rely on Epic System Pulse to monitor Epic?  For the simple reason that while System Pulse does a good job of collecting performance and health metrics across the Epic service it has no visibility into anything like shared SAN or shared network storage – one of the primary causes of EPIC application slowdowns.

What else could go wrong?   If your Clarity reporting application is running on a host connected via Fibre channel Host Bus Adapters (HBA) to a Brocade SAN switch which uses Virtual Channels, you might have a scenario where all existing HBAs may be sharing the same virtual channel resulting in significant congestion.  With help from Virtana Infrastructure Performance Management and by manually mapping FCIDs you could determine which Virtual Channels were being used by specific device ports.  This will help you determine if ports should be reallocated & additional HBAs deployed so that they may use other virtual channels.  Alternately you might have incorrect queue depth settings on the HBAs in the hosts running Clarity which may cause latency in the SAN fabric.  Virtana Infrastructure Performance Management can help you detect this and recommend the right queue depth settings to use.

What could go wrong outside the server (virtualized or physical), HBA and storage?  3^rd party backup software (for backup of Epic including the Caché database) may end up taking hours more than expected for the backup.  Virtana Infrastructure Performance Management could use time comparison charts to show you when there is a gap in the backup read workloads, using this data your backup manager could use trend data to identify what may turn out to be a timeout in the dedupe engine of the backup software.

The recurring theme in this article it is that there are many variables in the underlying infrastructure: servers, HBAs, SAN switches, networked storage, backup software – all outside the control of the Epic application which often contributes to latency and downtime in Epic.  Your goal then should be to catch any deviations and take proactive action before they spiral into downtime.  That is the motivation behind so many healthcare firms using Virtana Infrastructure Performance Management to monitor Epic and Cerner infrastructure. 

Important Gotta-Have Information

Drop us a line and we’ll be in touch! And don’t forget to follow us on Twitter, LinkedIn, and Facebook to stay up to date on the latest and greatest in hybrid AIOps.

The post Avoid downtime with EPIC Electronic Health Record (EHR) systems by using <em>Virtana Infrastructure Performance Management</em> appeared first on Virtana.

September 16, 2019

Earlier this month we announced the latest iteration of our award-winning hybrid IT infrastructure management and AIOps platform, VirtualWisdom. This was one of our biggest product-related announcements of the year, and we were thrilled with the response we received not only from our partners and customers, but also from the media and analyst community. Let’s take a look at what some folks had to say about the new VirtualWisdom.

First off, it’s worthwhile to highlight Enterprise Strategy Group’s Bob Laliberte’s insight into the overall AIOps and infrastrucutre monitoring market. As we’ve discussed previously, the modern hybrid data center model has taken full hold in the enterprise sector, which has led organizations to re-evaluate their entire approach to infrastructure management. According to Bob, AIOps is rapidly becoming enterprises’ path to managing the exponentially increasing scale and complexity of their hybrid infrastructures. But enterprises need to be able to implement AIOps-based monitoring solutions within the context and flow of their business. That’s where we come in.

“Considering enterprises’ persistent need for today’s mission-critical enterprise applications to be available at all times, infrastructure issues must be resolved in near real-time to avoid impacting the business and its customers,” says Bob. “The new VirtualWisdom will help enterprises apply the machine intelligence and expert systems needed to reap the benefits of AIOps-supported hybrid infrastructure management.”

Journalists also had some interesting things to say about our approach to AIOps. In his article for DevOps.com, Mike Vizard notes that a “day of reckoning” is coming for proponents of DevOps and IT teams that have built sprawling IT environments, and that advancements in AIOps should go a long way to bring the two schools of IT management together. It’s our intention to support those advancements , using VirtualWisdom’s advanced capacity forecast alarms and proactive dashboards to allow IT teams to respond to their changing application conditions in real time.

SearchITChannel’s John Moore highlighted some of more channel-focused features of VirtualWisdom 6.2. Specifically, John discussed the product’s new licensing approach through WisdomPacks – unique deployment packages that addresses specific customer monitoring needs without having to purchase a license for each virtualization engine. Joseph Tsidulko’s article for CRN also discussed the new WisdomPacks, highlighting that they are designed to make it easier for partners to deliver comprehensive artificial intelligence-powered IT monitoring and optimization offerings tailored to the needs of enterprise customers. These licensing updates follow the enhancements we made last year to our partner program to help improve partners’ margin opportunity and bolstered deal registration.

I’d like to close out this summary of the VirtualWisdom 6.2 launch with a word from Virtual Instruments’ SVP of Products, Tim Van Ash, who eloquently summarizes our vision for not only the future of our products, but the future of IT operations:

“The future of IT operations is autonomous: enterprises need IT operations that never fail to deliver mission-critical services, that adapt to business innovation, and consume resources ever more efficiently. As the scope of enterprises’ hybrid infrastructure management needs has expanded, we have continued to expand the breadth of our monitoring and inject meaningful AIOps capabilities into the VirtualWisdom platform. With the new VirtualWisdom, we are enabling enterprises to truly harness the power of AI and machine learning, with a view towards the automated IT operations of tomorrow.”

Click here to learn more about the new VirtualWisdom, and be sure to follow us on Twitter and LinkedIn to stay up to date on the latest and greatest in all things Virtual Instruments.

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