Operations | Monitoring | ITSM | DevOps | Cloud

Presto is an open source SQL query engine that runs analytics on large datasets queried from a range of sources, including Hadoop and Cassandra. Presto was originally developed by Facebook to run queries on its large Apache Hadoop data warehouse and is now used as an interactive analytics tool at companies like Airbnb, Uber, and Netflix.

As you navigate through Datadog, you may find that you want to dive into a graph to explore your timeseries data more deeply, or make quick changes to a graph without permanently altering it. To make it easier to explore the data in your graphs, we’re excited to introduce a newly revamped full-screen view for our timeseries graphs. You can now quickly and easily apply functions, navigate through time to find anomalies, and save and share your work.

Responsible for collecting various system and service metrics and forwarding them downstream to a backend storage system, the role metric collectors play in monitoring pipelines is crucial. Despite this fact, they often get left in the shadows cast by the beautiful frontend analysis tools like Kibana or Grafana. In the world of open source monitoring stacks, Metricbeat and Telegraf stand out as the most popular metric collectors. The truth is that they do much more than simply collect metrics.

Cloud environments are becoming increasingly complex, with applications and even infrastructures changing constantly. Despite their dynamic nature, these environments must be monitored constantly for teams to ensure the stability, security, and performance of workloads running in them. Tracking these infrastructure changes is one of the most important—and one of the most difficult—parts of maintaining a cloud environment.

One of the oldest (but often neglected) security vulnerabilities is SQL injection. One common scenario goes like this: An unsuspecting programmer writes an application that accepts input from the user which serves as a parameter to retrieve or store data from a database (e.g., a web login form). The programmer writes a dynamically populated SQL query inside the app, based on user input like username and password (see Image 1 for reference).

Monitoring an Azure environment can be a challenging task for even the most experienced and skilled team. Applications deployed on Azure are built on top of an architecture that is distributed and extremely dynamic. But all is not doom and gloom. Azure users have a variety of tools they can use to overcome the different challenges involved in monitoring their stack, helping them gain insight into the different components of their apps and troubleshoot issues when they occur.