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Why you should centralize your product development data
And break away from data isolation
The need to get your most important product development data under a common framework to make it more widely available for better control and governance has never been greater. But to enable this transformation, you need to set your IT operations management free.
As product development teams have adopted a wide range of tools for specific projects, including performance monitoring, UX, and user data monitoring, many of these teams are lacking an overall management framework.
The central IT department may not even be involved in the initial evaluation process for some of these tools, running the risk of having shadow systems within the organization.
This can lead to the rise of ad hoc processes, and a lack of central IT governance across IT infrastructure, data, and tools.
Start with a common framework
You need to get IT services under a common framework to make data more widely available for better control and governance because the data you need to analyze is probably available only in islands. But by using modern technologies and APIs, you can collect this data in a single repository where you can perform real-time analysis on it using model-driven algorithms. In this way, detecting anomalies in data becomes easier.
Running applications over a dynamic infrastructure allows scale-in and scale-out based on load factors. Even simple mistakes in the configuration of dynamic infrastructure and applications are hard to detect and can lead to costly outages.
Often, application owners know that there is a problem, but they cannot quickly pinpoint the cause. That is why it is necessary to adopt technologies that are using big data analytics in real-time to better manage the unknown problem.
Include 5 key capabilities in your reference architecture
Due to the sheer volume of data that operations management tools generate, product development teams need to include five key capabilities in their IT operations management reference architecture.
These include the ability to:
- 1. Collect: Consolidate data into a high-speed column store repository that can respond to queries within seconds.
- 2. Ingest: Ingest data from structured and unstructured data sources. Examples include metrics, logs, events, tickets, defects, and user experience.
- 3. Analyze: Implement operational analytics to identify anomalies and trending topics, correlate metrics from various sources against dynamic service models, and relate the solutions to the anomalies.
- 4. Robotize: Automate repetitive tasks using process automation to replace manual processes and fix known incidents with known solutions.
- 5. Visualize: Simplify visualization that ties the operations data to the business context.
Collect all the metrics
The key is to collect all the metrics and not exclude any, then use analytics to identify the ones with the highest correlation to service performance in real-world production systems.
The big issue is that it is hard to detect problems that may not have occurred before. Problems build up over time, and the root cause may be hidden in data that is a week old.
Often, operations look at symptoms, and analytics and visualization go together in such situations. Having the ability to go back in time and visualize when the systems started producing anomalies can help guide the operator to troubleshoot the problem faster.
Anomaly detection can help to prioritize defect resolutions and, when combined with business-prioritized key performance indicators (KPIs), prioritize the severity of the impacts, and focus the operations team on high-impact defects.
Take a platform approach to product development data
You need a platform approach to product development data that can ingest data from multiple islands, analyze data in real-time, and provide context—for example, for service desk, service monitoring, security risk assessment, etc.
The platforms must enable collaboration between departments via dashboards, communication tools, and more.
Platforms built on containers and microservices let you add new capabilities, upgrade without downtime, and even configure high availability.
Remember: Digital transformation is about speed and agility, driven by the customer experience of enterprise products and services.
By consolidating islands of isolated data, your organization gains the ability to continuously improve performance, availability, and the user experience.