A key driver of digital transformation initiatives is the desire to streamline application development and delivery in order to bring better, more secure software to market faster.
To achieve this, organizations have widely adopted DevOpsencompassing significant changes in team culture, operations, and tools used throughout the continuous development cycle.
More recently, teams have started applying DevOps best practices to infrastructure automation, giving developers a more active role with GitOps as an operational framework. Modern infrastructure should be elastic and GitOps approaches are used to automate infrastructure and application provisioning using Git, an open source control system, which provides change processes, including revisions and approvals. The key components of GitOps are declarative-as-code infrastructure, orchestration, and observability.
Observability is necessary for effective collaboration and automation
Site Reliability Engineering (SRE) relies on observability and automated observability configuration to find answers to questions such as “Did my deployment work?”, “Modifying improve the experience of our users?” or “Did the last update cause the app problem or something else?” But this is difficult to achieve on a large scale:
- Development teams need specific information about the microservices they are responsible for, reflecting metrics, dashboards, custom alerts, service level objectives (SLOs), or even automatic remediation steps. But setting up these tools requires in-depth knowledge and requires considerable effort if done manually.
- Operations and observability teams cannot provide the required customizations for hundreds of other teams. If they are unable to provide an automated self-service approach, they will not only fail to provide observability, but also fail to set organizational standards at scale.
Many observability solutions do not support an “as code” approach, require manual effort, or even make automated approaches impossible due to:
- Missing or limited API support for the configuration of the observability platform.
- Missing capabilities or lack of configuration templates that effectively manage configuration dependencies.
- Third-party tools required create additional complexity and considerable effort when configuring, maintaining or automating on a large scale.
Due to these issues, developers often lack control over the behavior of their monitoring platform. Configurations, such as custom metrics, service level indicators (SLIs), SLOs, dashboards, and alerting rules are often created manually without central management and do not meet business requirements.
Dynatrace enables software intelligence as code
Dynatrace uniquely delivers software intelligence as code by combining observability, AIOps (AI for IT operations), and application security. Organizations that adopt GitOps can leverage automated software intelligence and bring new features to market faster, with higher quality by ensuring information and repeatable common standards and goals. This enables effective DevSecOps collaboration, as well as observability-based automation against all critical metrics (speed, security, stability, availability, productivity, and business metrics) enterprise-wide.
As a result, Dynatrace customers can reduce application integration time from hours to minutes.. Considering that large organizations often have hundreds of applications in ever-changing multicloud environments, this is a massive accelerator that creates a foundation for improved cross-functional collaboration.
Dynatrace provides powerful API endpoints to configure the Dynatrace platform at scale for automated operations and observability. Configurations can be centrally managed as a single source of truth for easier review, including versioning support.
SRE teams can easily provide templates for custom configuration of specific components, for example, custom dashboards, metrics, alerts, SLOs or remediation steps. Application and DevOps teams can use and adapt these models to get specific insights and drive the automation of their applications while adhering to corporate standards.
Dynatrace further expands functionality to easily customize observability, application security and AIOps as code with the following upcoming enhancements:
New API endpoints to provide granular observability customization for containers and processes, web and mobile apps, server-side services and more. This builds on existing functionality, including configurable dashboards and business analytics via API.
Additional API endpoints to extend AIOps configuration, allowing DevOps teams to fine-tune anomaly detection and alerting based on management zone permissions, enabling a secure approach to self-service.
the open source command line interface for monitoring as code with Dynatrace to provide new features that allow SRE teams to provide self-service SLO management to DevOps teams.
Application security capabilities can be unlocked through the API, enabling automatic vulnerability management at scale.
Additional Dynatrace Cloud Automation-as-code integrations enable orchestration of DevOps toolchains, as well as automation of those toolchains based on observability and security measures.
How to start
All of the Dynatrace enhancements mentioned in this blog post will be available within the next 90 days.
If you’re not using Dynatrace yet, it’s easy to get started in less than five minutes with Dynatrace free try.