November 18, 2020 By Pratik Gupta 3 min read

Bringing automated application performance monitoring and observability capabilities to Watson AIOps.

Today, IBM announced a definitive agreement to acquire Instana*, an application performance monitoring and observability company. The acquisition will help businesses better manage the complexity of modern applications that span the hybrid cloud landscape and infuse AI in all areas of IT management.

The “holy grail” of IT management has been to automate as much as possible in order to become more proactive and productive. This more-automated model starts with a DevOps workflow that uses automation to create repeatable, reliable, predictable deployment. This workflow accelerates application development cycle times. This is useful to Site Reliability Engineering (SRE) teams writing scripts to automate operations issues so they can avoid an outage and getting paged in the middle of the night. This programmer mindset and its focus on automation has enabled and enhanced the delivery and operations of modern, highly scalable cloud applications.  

So why are a majority of enterprise workloads still being developed and managed the traditional way? Why has there been so little progress in automation of IT operations? Why are operations teams still struggling with the basics of application performance management and operating these critical systems?

Intelligent, AI-powered automation

The reason is that there are a vast number of tasks that need a more intelligent mechanism for automation. A simple rule of IFTTT (“If This Then That”) is no longer sufficient. Enter the modern artificial intelligence (AI), machine learning (ML) system.

AI has reached a level of maturity where IBM Watson Machine Learning models are capable of learning behavior, determining what ‘good’ is and then using that knowledge to suggest action or invoke an action directly. These AI models have the ability to learn, predict and automate a vast number of tasks — from DevOps processes to IT operations — augmenting the human’s ability to do the task or simply doing the mundane, repetitive tasks, leaving people to focus on higher-value work.  The success of AI and of humans to manage critical IT systems and applications depends on the information they have to analyze. In fact, some of the major causes of AI system failures are a lack of good quality data and poor data governance.

Modern observability and application performance monitoring platforms, like Instana, have been built from the ground up to take advantage of new technologies like Kubernetes and cloud-native microservices to fill critical gaps. Instana brings a host of leading capabilities, such as a comprehensive collection of application tracing and dependency, relating of logs, metrics and dependencies, automated and instant instrumentation, and it is designed for AI-based root cause analysis and high cardinality analytics.

Screenshots from the Instana performance monitoring and observability platform.

The Instana and IBM advantage

With the convergence of the Instana application performance monitoring and observability platform and IBM’s AI-powered automation portfolio, including Watson AIOps, IBM has assembled a strong set of technologies to transform the IT landscape, from the software development lifecycle to operations. This convergence will help enable enterprise IT environments to transform, realizing faster development cycles and better, more-reliable operations.

Instana brings continuous integration/continuous delivery (CI/CD) pipeline visibility to enable closed-loop DevOps automation, provides richer context that enables insightful intelligence and offers AI-based resolution to problems. It reduces complexity by automated discovery and dependency mapping across the hybrid cloud environment — from mobile to mainframe. Its high-performance architecture can capture 100% of transactions at one-second intervals across a large distributed application in a hybrid cloud, collecting billions of metrics a day, in real time, for analysis. The Instana ecosystem of data collectors supports popular, open-source technologies like Prometheus and OpenTelemetry. Their SaaS-based delivery model and on-premises deployment options provide client choice in adoption models.

The combination of the Instana platform and IBM Watson AIOps capabilities extends and enriches IBM’s AI-powered automation portfolio to deliver more advanced capabilities to help our clients move from reactive to proactive management of IT operations.

Learn more about IBM Instana Observability – Application performance monitoring.

Was this article helpful?
YesNo

More from Automation

4 key metrics to know when monitoring microservices applications running on Kubernetes

3 min read - Understanding how microservice applications works on Kubernetes is important in software development. In this article, we will discuss why observing microservice applications on Kubernetes is crucial and several metrics that you should focus on as part of your observability strategy. Why should you observe microservice health running on Kubernetes and what are the Kubernetes metrics you should monitor? Consider a large e-commerce platform that utilizes microservices architecture deployed on Kubernetes clusters. Each microservice, responsible for specific functionalities such as inventory…

Deployable architecture on IBM Cloud: A look at the IaC aspects of VPC landing zone 

5 min read - In the ever-evolving landscape of cloud infrastructure, creating a customizable and secure virtual private cloud (VPC) environment within a single region has become a necessity for many organizations. The VPC landing zone deployable architectures offers a solution to this need through a set of starting templates that can be quickly adapted to fit your specific requirements. The VPC Landing Zone deployable architecture leverages Infrastructure as Code (IaC) principles, that allow you to define your infrastructure in code and automate its…

Deployable architecture on IBM Cloud: Simplifying system deployment

3 min read - Deployable architecture (DA) refers to a specific design pattern or approach that allows an application or system to be easily deployed and managed across various environments. A deployable architecture involves components, modules and dependencies in a way that allows for seamless deployment and makes it easy for developers and operations teams to quickly deploy new features and updates to the system, without requiring extensive manual intervention. There are several key characteristics of a deployable architecture, which include: Automation: Deployable architecture…

IBM Newsletters

Get our newsletters and topic updates that deliver the latest thought leadership and insights on emerging trends.
Subscribe now More newsletters