Oct 12, 2021. By Anil Abraham Kuriakose
Today, the pace of digital transformation is accelerating at an incredible rate. As businesses digitalize, they demand a wide range of new services and business applications from IT, along with fast changes to those applications. The Cloud and DevOps enable this fundamental shift, dramatically increasing the speed and volume of change and driving an explosion in operational data. As a result, IT asset management has undergone several changes in the era of cloud computing. This situation raised a question on tools like CMDB is relevant or not. These arguments are because the current ITOps tools and processes are built on static IT environments, and cloud-based IT will demand new tools and requirements, or no tools are required. Challenges of traditional CMDB and Asset Management in the modern IT environment Traditionally the CMDB contains a snapshot of the configuration item (CI) record covering the resource attributes, ownership, relationship to other Cis, and major lifecycle timestamps like creation, decommissioned dates, and so on. This content is more or less static in nature. As cloud adoption increased, the CMDB lost relevance because it needed to deal with newer dynamic configuration items (CIs). The traditional approach to server, system, and network management has become irrelevant with the Cloud because infrastructure, platform, and software are all sold as 'as-a-service rather than individual components without vendor support. In addition, Infrastructure automation enables faster changes in the IT resource side. Due to this, new assets are being created faster, and systems get downscaled or upscaled at different times, based on loads and traffic. The other aspect of CMDB and asset management are end-user computing and management of end-user devices. The end-user computing area is getting more commoditized. With concepts like BYOD, maintaining and tracking end-users and devices is very difficult. Does CMDB Still Matter In The Cloudera? The design and implement a configuration management database (CMDB) strategy as part of your cloud operating model is still relevant. The main goals of asset and configuration management are to: Support IT process to improve the efficiency of the IT organization. Minimize the quality and compliance issues. Manage and track the optimal usage for the assets. But in Cloudera, many new requirements need to be included in the traditional CMDB strategy. The additional requirements of Cloudera CMDB are (1) managing new cloud-specific configuration items (CIs), (2) real-time and continuous discovery - get a snapshot of all the supported resources associated with the account at any point in time, (3) Temporary and Transient Asset Life Cycle Management, (4) Change Management and Change Risk Management in Cloud and (5) Retrieve the configurations and dynamic relationships of the resources. 1. Managing new Cloud Specific Configuration Items (CI) The standard CMDB inventory contains resources like server hardware, virtual machines, databases, and network equipment before Cloudera. With the Cloud, it is required to include additional resources like containers, microservices, serverless functions, queues, etc., that can go much beyond the general semantics and relationship of the traditional CMDB. 2. Real-Time and Continuous Asset Discovery The Discovery process includes scanning Physical on-premise components, Virtual assets, and cloud resources like IaaS, SaaS, PaaS resources. Since Cloud is very dynamic in nature, the assets will change very frequently. Therefore, if the IT team does not have real-time discovery capability, the CMDB will fail. 3. Temporary and Transient Asset Life Cycle Management Cloud brings many new sets of configured items like stake-less instances and transient clusters due to autoscaling. These CIs need not to insert in the main CMDB or be included in a separate transient CMDB. 4. Change Management and Change Risk Management Many times an approval process will include handling the cloud configuration changes. The approver should understand the risk and consequences involved based on the historical analytics. Also, creating a risk score (high, medium, and low) is required to quantify tolerable and acceptable risk and serve as the basis for the decision to deploy changes. Classify the highest-risk changes (those with the high business impact) by using AIOps to identify those that repeatedly result in instability for the top two to four business-impacting applications. With the AI-driven change risk management and change management process, every change is tracked and recorded in the Cloud CMDB for future analytics. 5. Retrieve the configurations and dynamic relationships of the resources. AIOps tools help the CMDB to use topology information from multiple sources, such as an observability tool and cloud sources, to reconcile them for greater predictive accuracy. These are runtime relationships and can be used for improving operational efficiency. Adoption of AIOps Drives the Cloud CMDB Maturity The emergence of Artificial Intelligence and AIOps enables to improve the autodiscovery and dependency mapping (DDM). Since the Cloud is a highly changing environment, developers starting different workloads randomly can easily discover and profiled to decide to include in the asset list or not. The AI-driven classification methodologies make the Cloud CMDB more accurate. With AIOps, the IT team can realize the true potential of the CMDB and evolve the IT service management in the modern IT organization. This AI-driven CMDB fuels the adoption of autonomous operations and brings the IT organization closer to the long-awaited promise of touch IT operations. The CMDB Is Here to Stay along with AIOps The Cloudera CMDB should be a trusted source for providing an updated inventory of IT devices and relationships when it is executed well. Even in cloudera, the CMDB plays a critical role in IT operations, including governance, risk management, and compliance. The Cloud service asset and configuration management will continue to be evolved with the modern CMDB and AIOps. To learn more about the Algomox AIOps , please visit our AIOPs platform page.