IBM
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4.3
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Aleksander M.
Advising and building Data, Automation & AI solutions for regulated industries | Legal precision, financial mindset & technical depthUnified Data Integration and Governance for Analytics and AI on OpenShift
The most helpful aspect is the ability to connect different data sources, prepare and govern data, and then use it for analytics or AI workloads within a consistent environment. Its integration with Red Hat OpenShift is also valuable because it provides flexibility for hybrid cloud deployments and allows organizations to run the platform in their own infrastructure.
AM
Aleksander M.
Advising and building Data, Automation & AI solutions for regulated industries | Legal precision, financial mindset & technical depthComprehensive Monitoring, Steep Learning Curve
I use IBM Instana for real-time application performance monitoring across our applications and infrastructure. It helps me track service dependencies, analyze distributed traces, identify performance bottlenecks, and investigate incidents more quickly. What I like most about IBM Instana is the level of automatic visibility it provides with relatively little manual configuration. The automatic discovery of applications, services, infrastructure, and their dependencies is especially valuable, as it quickly builds a clear picture of how the environment is connected. I also appreciate the combination of real-time monitoring, distributed tracing, and infrastructure metrics in one interface. This makes it easier to move from a high-level alert to the specific service, request, or infrastructure component causing the issue. The visual service maps and detailed transaction traces stand out because they make complex microservices environments much easier to understand and troubleshoot. The initial setup was very easy, taking just one day.
AM
Aleksander M.
Advising and building Data, Automation & AI solutions for regulated industries | Legal precision, financial mindset & technical depthEnterprise-Ready Prompt Lab for Comparing Models and Building Project-Based AI Solutions
What I like most about IBM watsonx.ai is that it gives you a relatively easy way to start working with different models and prompts, but it still feels like something designed for real enterprise use rather than just a simple demo tool. I use Prompt Lab mostly to compare how different models respond, adjust parameters and test different prompt approaches without having to build a separate application each time. I also like that everything can be kept within projects and later connected with a wider architecture, because in practice the model itself is only one part of the whole solution. You still need to think about access, data, deployment and how the application will actually use it, and watsonx.ai gives you a much better starting point for that than a standalone chat interface.
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