Red Hat introduced Red Hat Enterprise Linux 9, the Linux operating system designed to drive more consistent innovation across the open hybrid cloud, from bare metal servers to cloud providers and the farthest edge of enterprise networks.
Observability brings value to organizations as they look for ways to improve DevOps transformations. By "observing" a system, an organization can better understand the internal and external state through observability.
As we look into the future direction of observability, we are paying attention to the rise of artificial intelligence, machine learning, security, and more. I asked top industry experts — DevOps Institute Ambassadors — to offer their predictions for the future of observability. Below are 10 predictions:
Helen Beal, Chief Ambassador, DevOps Institute
I want to see a nexus between observability and value stream management. There is a duality in VSM that observability can help with; it's about flow and value realization. Value outcomes for customers are typically measured in terms of P&L, NPS ore reviews and referrals. But these are all lagging indicators. Observability has the ability to provide leading indicators, real-time data that tells us what a customer is experiencing right now and how it's about to affect their behaviour.
The use cases for AIOps are expanding beyond incident management and into customer experience, hence the call from Eveline Oerhlich to rename the segment predictive analytics. It's moving into the realm of RUM (real user monitoring) and value stream teams can use the data to prioritize their work based on direct customer feedback.
Mark Peters, Technical Lead, Novetta
Observability changes with systems. Containers through Docker, Kubernetes and orchestration systems improve the ability to monitor individual events and create observability. The future of observability lies not in more observability but in using better processes through ML and AI functions to observe the results of observability, finding and fixing issues faster than human monitoring can handle.
Ryan Sheldrake, Field CTO, Lacework
I think when we can truly map GitOps back from runtime and entirely correlate and verify (not simulate) that what is running is still exactly what passed all the automated verification and tests on the way to deployment and feedback is instant/automated, we can consider the system to be close to "self-healing."
Tiffany Jachja, Engineering Manager, Vox Media
Machine Learning observability is the future of observability. For example, today, only a few programming language runtimes support auto-instrumentation in distributed tracing. As a result, most developers in organizations adopting tracing practices for their software services are coupling business logic to infrastructure configurations in their code. This leads to code staleness, additional development time, and more requirements to continuously deliver.
Parveen Arora, Co-founder and Director, VVnT SeQuor
Observability is looked upon as a priority for DevOps-driven, agile development methodologies in the hopes of driving faster release cycles and delivering higher-quality software.
Supratip Banerjee, Solutions Architect, Principal Global Services
The Rise of AI in Observability — We can obtain the knowledge we require by applying AI to your observability data, automating monitoring practices, and surfacing actionable information to improve the customer experience. Automating every step of the way from creating the data to informing us of what we actually need to do, effectively reduces mountains of data to actionable information.
Vishnu Vasudevan, Head of Product Engineering and Development, Opsera
The future of observability will require a preventive problem ID using historical data patterns that can be easily identified. Emerging security and data protection incidents are creating toil. If observability practices can get teams to build stories around the translation of data analysis to easily understand the insights and influence action on any business decision — that's going to help significantly. Therefore, building a value-driven strategy for future iterations, especially around the customer data and relationship to different app features within the product, will help evolve observability over time. Continuously evaluating the business strategy through the context of observability is where the future needs to go.
Jose Adan Ortiz,Solutions Engineer, Akamai Technologies
As far as new developments in the open telemetry field, it is important to consider another fundamental pillar that is getting more and more significant for development teams, SREs, and stakeholders: security.
Security data, events, and CVEs must be integrated in the near future to provide a deep correlation with logs, metrics, and traces in order to maintain software components secure and free of vulnerabilities.
Maciek Jarosz, DevOps and Process Expert
As time passes and we learn more and more regarding good engineering practices, tops and flops of any given technology, and all that jazz. I'd say there will emerge some players who will possibly dominate the observability market.
Maybe those would be the big names of today, maybe some brave business people who dared to try their crazy ideas on the market — only time will tell.
Neelan Choksi, President and COO, Tasktop
Continuous improvement of fast feedback and flow will be key to fast learning and understanding — if decisions that have been made are making an impact on customer experience. The faster our design and development cycles, the faster we learn. The ability to rapidly develop minimal delightful products will continue to be a key factor to successfully launch new and innovative products.
Anshul Lalit, Head of Technology and Transformation, Kongsberg Digital
We're in the midst of a data revolution and observability is a growing demand field. It is quickly becoming a skill sought after due to the ever-increasing number of distributed systems and the operational complexity that goes along with that. In the foreseeable future, we can expect observability to become more commonplace in our lives. With the increasing sophistication of IoT devices, it is becoming more challenging to troubleshoot and debug issues with these devices. In response to this, we can expect observability to be developed to keep pace with IoT technology. As a result, we can expect observability to be a nearly ubiquitous service that will be delivered in a multitude of ways. It will be used to send data from IoT devices up to backend analytics processing and to visualize data analysis. We may even see this service as a standard feature for IoT devices or included with a smartphone or personal computer operating system.
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