Operations | Monitoring | ITSM | DevOps | Cloud

How do I write a query for log analytics?

Log management is the processes and tools that your DevSecOps team use to collect, store and manage log data. As they constantly assess your applications and systems for performance, log analytics comes into play to improve the efficiency and effectiveness of an organization, identify and troubleshoot problems, and monitor the health and performance of system. Looking for a proactive approach to find issues, bugs and threats? Interested in surfacing your business and user adoption insights?

What is a log analytics solution? A way to find and fix fast!

There is value in the machine data (logs and events) from your infrastructure and applications. However, storing and analyzing that data to extract that value can be a big (and expensive) undertaking for organizations. With log analytics, companies like yours can better understand your log data and take action to improve reliability and increase security. Log files are produced by applications, operating systems, networks and other components of a technology stack.

3 Ways You Can Use CRM Data Analysis To Increase Growth

Customer Relationship Management software can be more than just a tool for managing communication with consumers during the sales and marketing processes. It can be a resource that can help guide you towards better and more effective marketing campaigns and boost your sales numbers. Here are three ways any business that uses CRM software can use it to grow.

Trust, understanding, and love

As Charles highlights in his Financial Services Predictions blog, operational resilience is critical. The regulatory drive for defining, measuring and improving operational resilience is clear within Europe, outlined by EU DORA and UK FCA / PRA guidelines. The organisations who embrace this change can capitalise on real opportunities in the coming years; specifically, the opportunity to use data-driven insights to improve customer experience and proactively resolve issues before customer impact.

InfluxDB, Flight SQL, Pandas, and Jupyter Notebooks Tutorial

InfluxDB Cloud, powered by IOx, is a versatile time series database built on top of the Apache ecosystem. You can query InfluxDB Cloud with the Apache Arrow Flight SQL interface, which provides SQL support for working with time series data. In this tutorial, we will walk through the process of querying InfluxDB Cloud with Flight SQL, using Pandas and Jupyter Notebooks to explore and analyze the resulting data, and creating interactive plots and visualizations.

Upgrade Your IoT/OT Tech Stack: Replace Legacy Data Historians with InfluxDB

Manufacturing and industrial organizations are firmly in the era of Industry 4.0. The third wave of industrial revolution, which saw the introduction of computers, robots, and automation in industrial processes, has given way to instrumentation, and the use of advanced technologies, like machine learning (ML) and artificial intelligence (AI), using both raw and trained data, to enhance industrial processes.

Datadog on Data Engineering Pipelines: Apache Spark at Scale

Datadog is an observability and security platform that ingests and processes tens of trillions of data points per day, coming from more than 22,000 customers. Processing that amount of data in a reasonable time stretches the limits of well known data engines like Apache Spark. In addition to scale, Datadog infrastructure is multi-cloud on Kubernetes and the data engineering platform is used by different engineering teams, so having a good set of abstractions to make running Spark jobs easier is critical.

Compactor: A Hidden Engine of Database Performance

This article was originally published in InfoWorld and is reposted here with permission. The compactor handles critical post-ingestion and pre-query workloads in the background on a separate server, enabling low latency for data ingestion and high performance for queries. The demand for high volumes of data has increased the need for databases that can handle both data ingestion and querying with the lowest possible latency (aka high performance).