Observability Solutions Simplify the New Distributed IT

Summary Bullets:

Charlotte Dunlap – Principal Analyst, Application Platforms

• Over the next six to 12 months, 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

• The future of observability is ML-powered predictive and prescriptive analytics to enable proactive responses that prevent problematic incidents

Accelerated digital business transformations are steering operations teams towards new observability stacks to oversee an increasingly diverse and distributed IT portfolio. Ops teams are overwhelmed with the move from monolithic apps to microservices where various service components within a single app must be secured and managed. New monitoring tools are emerging to help developers collaborate under DevOps models and gain automated visibility into the impact of modern coding on underlying systems. Observability solutions will shorten the lengthy feedback cycle involved before committing apps to code, enhancing the quality of apps moving through the pipeline.

Advancements shining the spotlight onto observability include integrated analytics with monitoring solutions; broad industry acceptance of interoperability OSS technology, including OpenTelemetry; innovative startups disrupting the traditional monitoring space; and growing complexities around IT infrastructures’ ability to support continuous delivery of apps from a data collection/monitoring perspective. 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 interactions. Participants of DevOps efforts are forced to reexamine how they implement observability earlier in the application lifecycle to improve insight in the underlying infrastructure.

Early thought leaders in this space 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).

New services are appearing 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, particularly through standards like OpenTelemetry, helps ensure interoperability between the numerous monitoring tools available in the market. This is important because proprietary solutions and the threat of vendor lock-in have resulted in an impediment of adoption of distributed monitoring/tracing. OSS technology is helping ensure consistency between trace data and log signals so that information can be turned into a metric to determine overall service behavior.

These events provide the foundation for the industry’s newfound focus on observability’s three basic objectives: automation, contextualizing information, and intelligent response. Solutions which fall into this category aim to automate every aspect of the monitoring products, a trait which serves as the core differentiator from traditional APM solutions. This scenario makes IT teams better prepared for event-driven architectures including tracking the flow of events triggered, diagnostics, and resolution, increasingly in an automated fashion.

Over the next six to 12 months, 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.

GlobalData has completed an Advisory Report which outlines the growing role of observability with app modernization including market drivers, key open-source technologies, and early thought leaders. (Please see Integrated Observability Systems Help Make Sense of Distributed IT Portfolios, September 3, 2021.)

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