Lightstep this week announced general availability of a Change Intelligence observability platform based on a time-series database that is capable of processing a trillion events each day.
Ben Sigelman, Lightstep’s CEO, said as IT environments become more complex, thanks to the rise of microservices and cloud-native computing platforms, existing monitoring and observability tools will not be able to keep pace with the rate of change in what have become highly dynamic IT environments.
While AIOps promises to address that complexity by employing machine learning algorithms to analyze IT environments and surface recommendations, Sigelman said there will always be the need for observability platforms that enable IT teams to discover the root cause of an issue in a way that surfaces the insights needed to fix the problem in real-time.
The Lightstep database was built by the same team that created Monarch, the globally-distributed in-memory time series database system that Google employs to monitor its applications and systems. Lightstep’s database makes it possible to collect metrics, in the form of distributed traces, at a level of scale that allows IT teams to analyze events across a distributed IT environment made up of both monolithic and microservices-based applications, said Sigelman.
Lightstep is the latest entrant in an already crowded field of observability platforms, all seeking to consolidate the wide range of monitoring tools IT teams have used for decades.
The challenge IT teams face is that each of those monitoring tools is focused on a narrow range of platforms. IT teams often lack context when an issue arises, and wind up trying to correlate reports from multiple monitoring tools in the hopes of discovering the root cause of an issue. Observability platform providers are making the case for a single platform that correlates application and infrastructure events in a way that makes it easier for IT to fix issues faster.
Observability, of course, has been a core tenet of DevOps for years. The tools for achieving that goal, however, have been cumbersome to implement and maintain using legacy application performance management (APM) platforms. Most of those platform providers, have rolled out what are positioned as next-generation observability platforms. Now, IT organizations will need to decide if they want to maintain investments in existing platforms versus moving to one of the raft of upstarts looking to dethrone APM incumbents.
The startups are counting on a massive expansion in demand for observability platforms. IT organizations have tended to limit their usage of APM platforms to mission-critical applications due to cost and the challenges associated with maintaining the agent software needed to collect metrics from each application. Modern observability platforms have automated much of the metrics collection process, while open source software promises to make metrics collection more affordable..
The challenge, of course, is that many organizations are already struggling to manage complex IT environments, and can’t necessarily wait for that open source software to mature.