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Sumo Logic Flex Pricing: Is usage pricing a good idea?

When discussing observability pricing models, there are three dimensions that must be considered The first, Cost per Unit, is an easy-to-understand metric, but in practice it is often overshadowed by a lack of transparency and predictability for other costs. The question is simple: how does a usage based pricing model impact these variables?

How To Harness the Full Potential of ELK Clusters

The ELK Stack is a collection of three open-source projects, Elasticsearch, Logstash, and Kibana. They operate together to centralize and examine logs and other types of machine-generated data in real time. With the ELK stack, you can utilize clusters for effective log and event data analysis and other uses. ELK clusters can provide significant benefits to your organization, but the configuration of these clusters can be particularly challenging, as there are a lot of aspects to consider.

Why Organizations are Using Grafana + Loki to Replace Datadog for Log Analytics

Datadog is a Software-as-a-Service (SaaS) cloud monitoring solution that enables multiple observability use cases by making it easy for customers to collect, monitor, and analyze telemetry data (logs, metrics and traces), user behavior data, and metadata from hundreds of sources in a single unified platform.

Top 10 Change Management Tools

Changes to software are inevitable and fundamental part of growth for any organization, however, change is often not straightforward. It can affect numerous aspects of a company and requires collaboration among all stakeholders. This is where change management tools come in to assist you with this. There’s currently a wide range of change management tools available, each providing benefits to specific scenarios and weaknesses to others.

Control your log volumes with Datadog Observability Pipelines

Modern organizations face a challenge in handling the massive volumes of log data—often scaling to terabytes—that they generate across their environments every day. Teams rely on this data to help them identify, diagnose, and resolve issues more quickly, but how and where should they store logs to best suit this purpose? For many organizations, the immediate answer is to consolidate all logs remotely in higher-cost indexed storage to ready them for searching and analysis.

Aggregate, process, and route logs easily with Datadog Observability Pipelines

The volume of logs generated from modern environments can overwhelm teams, making it difficult to manage, process, and derive measurable value from them. As organizations seek to manage this influx of data with log management systems, SIEM providers, or storage solutions, they can inadvertently become locked into vendor ecosystems, face substantial network costs and processing fees, and run the risk of sensitive data leakage.

Dual ship logs with Datadog Observability Pipelines

Organizations often adjust their logging strategy to meet their changing observability needs for use cases such as security, auditing, log management, and long-term storage. This process involves trialing and eventually migrating to new solutions without disrupting existing workflows. However, configuring and maintaining multiple log pipelines can be complex. Enabling new solutions across your infrastructure and migrating everyone to a shared platform requires significant time and engineering effort.

Optimizing cloud resource costs with Elastic Observability and Tines

In today's cloud-centric landscape, managing and optimizing cloud resources efficiently is paramount for cloud engineers striving to balance performance and cost-effectiveness. By leveraging solutions like Tines and Elastic, cloud engineering teams can streamline operations and drive significant cost savings while maintaining optimal performance.

Charting New Waters with Cribl Lake: Storage that Doesn't Lock Data In

There is an immense amount of IT and security data out there and there’s no sign of slowing down. Our customers have told us they feel like they’re drowning in data. They know some data have value, some don’t. Some might have value in the future. They need some place cost-effective to store it all. Some for just a short while, some for the long haul. But they’re not data engineers. They don’t have the expertise to set up and maintain a traditional data lake.

Driving SaaS Excellence Through Observability

For SaaS platforms, utilizing observability is crucial, as it’s vital for these companies to deeply understand their users' experience and the root cause of any issues. Observability involves leveraging the appropriate tools and processes in place to effectively track, examine, and troubleshoot the performance and behavior of a system, even if you can't directly see what's happening inside it.