Application Performance Monitoring (APM) and DevOps are drawing a lot of interest in the IT community that is looking for ways of delivering faster and more reliable information services. DevOps largely bridges the gap between the Development and Operational Deployment activity through automation. DevOps is enabling the rapid delivery of software through Continuous Integration and Deployment with some limited forms of largely system level monitoring. Application Performance Monitoring (APM) is another rapidly emerging technology solution that enables the ability to deliver a more reliable service through application level metrics and monitoring to help accelerate incident resolution, detect performance issues and diagnostics – APM addresses issues that traditional monitoring and logging do not adequately cover. Adoption of APM solutions has been fast furious driven in large part through easy to consume cloud enabled SaaS services such as AppDynamics, New Relic, Loggly, LogEntries, SumoLogic, Boundary and many other options including open source alternatives like Elasticsearch, Kibana and Logstash (ELK) amongst others.
However, both DevOps and APM fall short in providing a truly holistic and light-weight operations solution.
Hard-core systems operations and management that typically include patching, vulnerability management, backups/restore and continuous security monitoring as well as the financial management of the platform are largely left out. This is a serious gap in the current “state-of-the-art” given than typically 60-70% of a total system cost is associated with the Operations & Maintenance activity. Although, ITIL is a robust framework that got some traction in the operations management arena in the past decade, it is arguably heavy weight, considered costly and lacks agility. Just like DevOps emerged as a logical implementation level methodology to deliver agile application services through automation, ServiceOps provides an integrated and data-driven framework for platform operations that integrates with DevOps.
The key technology drivers for ServiceOps are Cloud Computing and Big Data — as the infrastructure becomes more software driven and telemetry data is easily available across the whole “stack”; we now have the ability to collect, process and actionize large amounts of data – the foundation elements of ServiceOps are in place.
ServiceOps is an implementation and delivery focused methodology that uses full-stack telemetry data and automation to help organizations deliver a reliable, secure and cost-effective IT service that is continuously optimized and includes End-User, System, Security and Financial operations.
For example in the area of pay-as-you-go cloud computing models, the ability to optimize the performance of cloud-based applications pays rich dividends in operational savings. Some organizations report being able to save up to 20% of their IaaS spend through a rigorous monthly tracking & optimization ensuring that “orphaned storage”, right-sizing VM’s,and using the right pricing model. Most IT organizations are ill-equipped and not focused on the financial aspects of cloud computing. Similarly, there are serious emerging challenges in the security operations arena – traditional security frameworks tend to be reactive in nature – the ability to perform forensic and trending analytics have been primary use cases. But with the advent of the NIST cybersecurity framework, high-profile incidents like Target and the increased cyber threat, organizations must implement real-time, automated solutions to contain the security costs and yet deliver a viable “armor” against threats.