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StAIble's AIOps Radar Part 3: First Platforms
In this blog, we'll focus on logging solutions and metrics & observability solutions.
StAIble's AIOps Radar Part 1: First Steps
In this blog, we'll show how you can modernise your operations with the tools you might already have!
When talking about starting with AIOps, it often brings up more questions than answers. How? Where? With what? That's exactly why we at stAIble decided to roll up our sleeves and put together a three-part series to help you navigate the AIOps journey.
Starting with this blog, we're diving into the "First Steps" of AIOps, drawing on the foundation we laid in our previous discussion on AIOps maturity levels. Our aim? To show you how you can start leveraging AIOps with the tools you might already have, making your journey a little less daunting.
For Who: Elastic AIOps is most suited for organizations already entrenched in Elastic’s ecosystem. Its unparalleled logging capabilities make it ideal for those prioritizing search and troubleshooting within vast data landscapes.
AIOps Features: Elastic AIOps excels in logging, utilizing AI to sift through data, enhancing the identification and troubleshooting process. While its observability suite covers metrics, logs, and traces, the AI-driven insights mainly enhance logging efficiency.
Our Opinion: Elastic is a strong player in the logging field, making it a great starting point for those already familiar with the Elastic environment. The tool is great for deep insights from logging analytics, but we tend to agree with online complaints about the user interface, highlighting the balance between features and user experience.
For Who: Opsgenie is tailored for teams already using Atlassian’s suite of tools. It's particularly beneficial for handling a high volume of alerts and streamlining incident management processes.
AI Features: Although not primarily an AI tool, Opsgenie’s strength lies in log grouping and managing alerts efficiently. It integrates AI to some extent in sorting and prioritizing alerts, making it a vital component in an AIOps strategy.
Our Opinion: Opsgenie stands out for its integration within Atlassian’s ecosystem, making it a strategic choice for current users. However, its focus is more on alert management than on full-spectrum AIOps capabilities, making it a complementary tool rather than a standalone AIOps solution.
For Who: Azure Monitor is designed for organizations deeply integrated with Microsoft's Azure services. It’s a fit for those seeking to add AI-driven insights into their cloud monitoring efforts.
AI Features: Azure Monitor incorporates machine learning to assist in anomaly detection and performance insights, albeit as part of a larger, paid feature set within the Azure ecosystem.
Our Opinion: For Azure loyalists, Azure Monitor adds valuable AI capabilities to cloud operations, albeit at an additional cost. The tool’s integration with Azure makes it a convenient choice, though businesses must weigh the benefits against the incremental costs of its ML features.
For Who: Amazon DevOps Guru is an optimal choice for AWS users looking to introduce AI into their DevOps practices. It’s tailored for those seeking to leverage AWS’s infrastructure for enhanced operational insights.
AI Features: Similar to Azure Monitor, DevOps Guru offers AIOps services that analyze operational data for anomalies and insights, albeit within AWS’s ecosystem. It's not a full AIOps platform but provides critical services to AWS users.
Our Opinion: DevOps Guru is a pragmatic step for AWS users into AIOps, offering a blend of AI services to enhance operational efficiency. However, it shares the common critique of platform-specific tools — limited to enhancing operations within its native cloud environment, with costs to consider.
For Who: Active Assist targets Google Cloud Platform users, though its precise AIOps functionalities remain somewhat vague compared to its competitors.
AI Features: Active Assist's role in the AIOps landscape is less defined, focusing on optimizing cloud operations with recommendations rather than offering a comprehensive suite of AI-driven operations tools.
Our Opinion: Active Assist’s potential in AIOps is intriguing yet under-specified. For organizations deeply embedded in Google Cloud, it may offer valuable optimizations, but its exact role and capabilities in AIOps require clearer definition to stand out as a recommended tool on the AIOps journey.
In our dive into "First Steps" for adopting AIOps, we've highlighted tools from platforms that many organizations already utilize. But embracing AIOps isn't just about leveraging existing products or adding new ones. An integral part of initiating AIOps involves creating custom scripts and setting up direct integrations. This approach enables organizations to start benefiting from AIOps by enhancing their current setup, sidestepping the immediate need for new purchases.
Stay tuned for the next part of our series, "First Tools," where we'll shift our focus to standalone tools that offer unique value and could be a great addition to your AIOps toolkit. Whether you're just starting or looking to expand your AIOps capabilities, stAIble is here to guide you every step of the way.
