Modern monitoring tools are emerging to help developers collaborate under DevOps models and gain automated visibility into the impact of modern coding on underlying systems.
Reports of business transformations shrinking from two years to two months during the pandemic are impressive, but the exceptional speed also presents the opportunity for devastating security breaches and problematic application and infrastructure issues.
Traditional application monitoring technologies such as application performance management (APM) have taken a backseat in the cloud’s evolution in recent years to more important breakthroughs such as Kubernetes containerization, cluster management, low-code, and intelligent automation platforms. Now operations teams struggling to adapt their IT infrastructure to accommodate a continuous delivery model are seeking modern monitoring tools in the form of observability solutions for detecting anomalies early on and instantaneously providing feedback and alerts.
The transition from monolithic to microservice and serverless app architectures is causing a surge in the volumes of data that must be collected to reflect the state of the system as well as the complexity of the analysis required to produce meaningful insights. Ops teams are required to secure and manage numerous service components within a single app, and developers are burdened with complex infrastructure coding in order to glean monitoring and tracing data on the performance and systems interactions of their apps.
More tools for DevOps
New services are descending to improve insights into microservices performance issues, guiding broader DevOps teams via sets of metrics reporting both good and bad performance. Based on monitoring agents and data collectors dropped into a particular environment to detect host-level metrics, alert notifications are delivered via email or collaboration tools such as Slack. The integration of telemetry into modern solutions with standards like OpenTelemetry ensures interoperability between the numerous monitoring tools available in the market.
Early thought leaders span from modern APM and cloud platforms providers aiming to enhance their core hybrid and multi-cloud offerings (IBM Instana, Red Hat Insights/Ansible, and Oracle Cloud Observability) to powerhouse startups set to disrupt the traditional monitoring space (Honeycomb, Lightstep, and Chronosphere).
In the coming year, the observability market segment will evolve to include more comprehensive solutions which provide application-level observability data alongside systems-level data, delivered through pre-set parameters. Integrated observability will support event streaming to detect anomalies and instantaneously highlight areas of concern through ML by measuring baseline thresholds and learning over time via modeling when things are not consistent. The future of observability is around ML-powered predictive and prescriptive analytics to enable proactive responses that prevent incidents.
A number of drivers and enablers of observability include a change from data-based to event-based architectures and increased focus on infrastructure as code in support of a shift-left IT model which lets developers play a greater role in application lifecycle management, as in testing earlier in the software development process. These moves toward emerging observability are helping it become a relevant part of the cloud’s value chain and an important technology to watch.