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For most big data enterprises, application performance management (APM) is considered an essential element of application-centric IT operations and a DevOps-enabling bridge between production and development on one side, and IT and digital business on the other. APM strives to detect and diagnose complex application performance problems to maintain an expected level of service, and in doing so, APM can reduce mean time to repair (MTTR), reduce IT maintenance and infrastructure costs, and improve business outcomes.
It’s been said that almost every business now is a software business in some form or another. That means that the reliability and performance of your software applications are critical to your success. From this perspective, APM solutions can deliver a significant return on investment (ROI) if used to their full potential. Strictly speaking, the ROI is the ratio between the net profit of an investment and what it cost to implement it. It is often expressed as a percentage, to represent how much profit was made compared to the costs.
ROI for IT Investments is Different
Traditionally, when IT professionals and executive management discussed the ROI of an IT investment, they were dealing primarily with hardware/infrastructure and mostly thinking of “financial” benefits. Financial benefits include impacts on the organization’s budget and finances, e.g., cost reductions or revenue increases.
With the rise of software-defined everything and cloud-based service offerings, business leaders and technologists also consider the “non-financial” benefits of IT investments, including impacts on operations or mission performance and results, e.g., improved customer satisfaction, better information, shorter cycle-time. These are the so-called “intangibles”, “soft”, or “unquantifiable” benefits of information technology. Unlike financial returns, there may be no widely-accepted metrics that can be applied. However, IT’s potential for producing positive impacts on business performance is undeniable. Both financial and non-financial benefits must be taken into account to fully assess the value of any technology solution, and APM is no different.
Enabling Big Data DevOps ROI with APM
Large enterprises typically run multi-tiered applications across a variety of systems and platforms. These can range from in-house systems to external clouds. With the accelerating use of cloud-based apps, the complexity of integrating these applications is a challenge for even the most sophisticated IT teams. Greater agility is the underlying business case for a DevOps approach. Leveraging increased automation, DevOps applies agile and lean practices throughout the software lifecycle. It allows IT to launch higher quality applications and deploy them faster than in the past.
As more organizations discover the efficiencies of adopting DevOps best-practices for application lifecycle management, they quickly realize that APM enables DevOps ROI. Similarly, IT operations teams are recognizing the value of APM to manage expensive cluster resources more efficiently and to better inform DevOps teams who depend on reliable and consistent infrastructure availability and performance.
Align Your Compute Resources and Costs with Actual Service Demands
Pepperdata APM solutions are not only helpful for measuring the performance of your applications and helping to identify opportunities for improvement, they can also deliver more tangible “financial” ROI by reducing your infrastructure and hosting costs through analysis and optimizations. Applications and IT infrastructure must work together. IT resources represent both capital and operational expenses, putting more pressure on IT organizations to optimize the use of existing resources and acquire new resources only when required.
Pepperdata Capacity Optimizer is a capacity management solution that aligns IT resources with service demands, optimizing resource utilization, and reducing costs. Capacity Optimizer leverages active resource management features in Hadoop to dynamically tune cluster resources and eliminate inefficiencies and bottlenecks. Running continuously, it improves the capacity utilization of your existing production clusters without manual tuning or intervention. Enterprise deployments typically achieve a 30-50% increase in throughput performance on existing hardware with Capacity Optimizer, enabling them to save thousands of dollars in unnecessary infrastructure and services expenditures.
Only Pay for the Cloud Resources You Need
For organizations migrating to the cloud, Pepperdata Capacity Optimizer provides an even more compelling benefit. It’s easy to forgive IT Ops for over-provisioning on-premises compute resources to avoid an application bottleneck. On-prem resources represent a sunk cost and are already paid for, so the worst that can happen is an up-tick in chargeback. But taking the same approach to cloud-based resources will yield a nasty surprise in the form of an unexpectedly high monthly bill from your cloud service provider who charges you for every memory and CPU instance that you’ve subscribed to, whether you need and have used those resources or not.
Capacity Optimizer ensures that you are only using the compute resources in the cloud (and on-prem) that you actually need to achieve optimal application performance. When you assess your priorities for monitoring and managing your technology stack, remember that the only thing that your customers see, and thus the only thing that they care about is the performance of the application they’re using. Whatever may be happening in your big data stack, the application is where the rubber meets the road.
Fine-tune your big data application environment and achieve tangible ROI with Pepperdata Capacity Optimizer by understanding exactly what CPU and memory resources each application requested, what it needs, what it used, and what it wasted, and identify the true impact on your big data application performance.