Sumo Logic announced today it has extended the reach of its monitoring platform to provide deeper insights across application and infrastructure logs, metrics, traces and metadata in real-time.
The latest additions to the company’s suite of software-as-a-service (SaaS) offerings include Sumo Logic AWS Observability Solution, which focuses exclusively on AWS services, and additions to the Sumo Logic Software Development Observability Solution that provide support for GitHub, Jenkins and PagerDuty alongside existing support for Jira, Bitbucket and OpsGenie. The Sumo Logic Software Development Observability Solution is based on a key performance indicator (KPI) methodology developed by the DevOps Research and Assessment (DORA) organization, an arm of Google.
In addition, Sumo Logic has launched a closed beta for a Distributed Transaction Tracing service based on the OpenTelemetry standard that will integrate logs, metrics and metadata. Finally, the company has added more tracing capabilities to its existing Microservices Observability Solution.
Sumo Logic got its start by providing a cloud service for analyzing logs as an alternative to Splunk. Since then, the company has extended the scope of its services to address a wider range of observability requirements for DevOps teams.
Ben Newton, director of field evangelism for Sumo Logic, said the company is trying to engage IT organizations at any level of maturity by providing access to a range of offerings from log analytics to observability tools for various platforms including Kubernetes. Those offerings now span the application life cycle from coding to grave, he said.
Sumo Logic also differentiates a pricing model based on data tiers that enables IT teams to analyze logs, metrics and traces across a variety of use cases without monthly limits, peak provisioning or on-demand charges for data volume overages or exceeding custom metrics limits.
In the wake of the economic downturn brought on by the COVID-19 pandemic, the rate at which DevOps tools have been shifting into the cloud has accelerated. With more DevOps teams working from home, cloud-based services are more flexible. At the same time, more organizations prefer to treat IT costs as an operating expense at a time when the overall economic outlook remains uncertain. The entire IT organization needs to be able to respond to rapidly changing business conditions in a more agile manner, noted Newton.
Less clear is whether the economic downturn might also drive consolidation across what today is a spectrum of observability tools spanning log analytics to application performance management (APM) platforms used primarily to sample application traffic. It’s even less clear whether the rise of distributed tracing capabilities might reduce dependency on application sampling altogether.
What is apparent is IT teams have never had more visibility into IT environments that increasingly are more complex. The challenge and opportunity now is determining how best to apply a wide range of observability tools to turn all that insight into actionable intelligence.
