Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.
Dynatrace today announced it has extended its observability capabilities via the launch of its PurePath 4 platform that adds support for the open source OpenTelemetry framework and W3C Trace Context specification for distributed tracing.
In addition, the company is adding support for service meshes and serverless computing frameworks running on Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform.
Alois Reitbauer, chief technology strategist for Dynatrace, said by adding support for open source tools to gather metrics, the total cost of achieving observability is being driven lower at a time when a transition to microservices-based applications is making the need to observe applications more crucial than ever.
Dynatrace is adding support for OpenTelemetry and W3C Trace Context to a platform that has already supported distributed tracing since 2006 via its OneAgent software. Dynatrace is now becoming the latest provider of observability tools to embrace open source software to instrument applications as part of an effort to focus engineering efforts on advancing analytics capabilities.
In the case of Dynatrace, those capabilities are driven by a Davis artificial intelligence (AI) engine embedded within the Dynatrace platform and SmartScape continuous topology mapping technology. The combination of those technologies makes it possible for Dynatrace to automatically discover changes to IT environments and surface the root cause of any issue that might arise, noted Reitbauer.
Despite being widely available via application performance monitoring (APM) tools, distributed tracing is now coming into vogue. As application environments become more complex, there is a need to more deeply analyze events to discover the root cause of an outage or performance issue.
The challenge has been that applying that level of instrumentation to applications has been costly. Many IT organizations have historically limited the use of APM tools to their most mission-critical monolithic applications. It’s also worth remembering that three-tier applications are easier to troubleshoot because the potential source of any issue is probably already well-known to the IT team, he added.
Given all the dependencies that exist between microservices, however, Reitbauer said the need to understand what’s occurring within an application environment more deeply is becoming a bigger requirement.
Observability, of course, has always been a core tenet of best DevOps practices. The level of observability depth required by DevOps teams has tended to vary widely. Increased adoption of microservices-based applications invariably will push more IT organizations toward embracing DevOps at increasing levels of sophistication and maturity.
In the meantime, the observability wars among platform providers are intensifying. There’s no shortage of options to achieve that observability, so it will be up to each IT team to decide which platform might best suit their DevOps workflow. Dynatrace is betting that as more applications become instrumented, deciding which platform to employ will shift closer to the AI capabilities that enable issues to be resolved issue faster regardless of what type of application is deployed rather than the capabilities of the agent software employed to instrument applications.
