Raygun
Sentry.io
Rollbar
Datadog
BugSnag
AirBrake
NewRelic
Logentries
Apache Flink
Apache Spark
Amazon Kinesis
Spring Framework
Spark Mail
Apache Airflow
Grails
Apache Kafka
Raygun Apache FlinkBased on our record, Apache Flink should be more popular than Raygun. It has been mentiond 27 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Raygun is a cloud-based platform that makes sure your web and mobile applications are free of errors, as well as your users are satisfied. It specializes in JavaScript error monitoring and offers a wide range of features to help you easily detect and fix issues. - Source: dev.to / 4 months ago
We can make the process a little easier by using our agile processes together with a continuous deployment strategy. For example, our friends at Raygun, discovered that “when a team gets locked into a sprint it can become much harder to recognize and fix bugs”. - Source: dev.to / 8 months ago
Regarding your last question, when I mention sub-processors who we don't have an SCC with I'm thinking about vendors like RayGun. It's a system we use to monitor alerts and warnings coming from our app when in the hands of our end-users. We have configured the tool so we get absolutely no personal information - no names, emails, id's or any of that sort. It's nothing more than technical data dumps from the inner... Source: over 1 year ago
Error logging and monitoring are crucial for any application, Appwrite being no exception. We wanted to make it extremely easy to collect and monitor your logs while staying true to our philosophy of being completely platform agnostic. With Appwrite 0.12, we've introduced support for some amazing open source logging providers like Sentry, Raygun and AppSignal! - Source: dev.to / over 2 years ago
We have RayGun for logging/reporting on the client-side of the apps. They are showing nothing interesting from those devices. They seem to fail silently. Source: almost 3 years ago
Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / 23 days ago
Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 3 months ago
Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 4 months ago
Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 5 months ago
Due to the technology transformation we want to do recently, we started to investigate Apache Iceberg. In addition, the data processing engine we use in house is Apache Flink, so it's only fair to look for an experimental environment that integrates Flink and Iceberg. - Source: dev.to / 5 months ago
Sentry.io - From error tracking to performance monitoring, developers can see what actually matters, solve quicker, and learn continuously about their applications - from the frontend to the backend.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Rollbar - Rollbar collects errors that happen in your application, notifies you, and analyzes them so you can debug and fix them. Ruby, Python, PHP, Node.js, JavaScript, and Flash libraries available.
Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.
Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.