Rancher Reviews

Apache Flink Reviews

Rancher mentions (24)

• Terraform code for kubernetes on vsphere?

  I don't know in which extend you plan to use Kubernetes in the future, but if it is aimed to become several huge production clusters, you should looks into Apps like Rancher: https://rancher.com. Source: almost 2 years ago

• I want to provide some free support for community, how should I start?

  But I think once you have a good understanding of K8S internal (components, how thing work underlying, etc.), you can use some tool to help you provision / maintain k8s cluster easier (look for https://rancher.com/ and alternatives). Source: almost 2 years ago

• Don't Use Kubernetes, Yet

  A few years, I would have said no. Now, I'm cautiously optimistic about it. Personally, I think that you can use something like Rancher (https://rancher.com/) or Portainer (https://www.portainer.io/) for easier management and/or dashboard functionality, to make the learning curve a bit more approachable. For example, you can create a deployment through the UI by following a wizard that also offers you... - Source: Hacker News / almost 2 years ago

• Building an Internal Kubernetes Platform

  Alternatively, it is also possible to use a multi-cloud or hybrid-cloud approach, which combines several cloud providers or even public and private clouds. Special tools such as Rancher and OpenShift can be very useful to run this type of system. - Source: dev.to / almost 2 years ago

• Five Dex Alternatives for Kubernetes Authentication

  Rancher provides a Rancher authentication proxy that allows user authentication from a central location. With this proxy, you can set the credential for authenticating users that want to access your Kubernetes clusters. You can create, view, update, or delete users through Rancher’s UI and API. - Source: dev.to / almost 2 years ago

Apache Flink mentions (30)

• Show HN: Restate, low-latency durable workflows for JavaScript/Java, in Rust

  Restate is built as a sharded replicated state machine similar to how TiKV (https://tikv.org/), Kudu (https://kudu.apache.org/kudu.pdf) or CockroachDB (https://github.com/cockroachdb/cockroach) since it makes it possible to tune the system more easily for different deployment scenarios (on-prem, cloud, cost-effective blob storage). Moreover, it allows for some other cool things like seamlessly moving from one log... - Source: Hacker News / 2 days ago

• Array Expansion in Flink SQL

  I’ve recently started my journey with Apache Flink. As I learn certain concepts, I’d like to share them. One such "learning" is the expansion of array type columns in Flink SQL. Having used ksqlDB in a previous life, I was looking for functionality similar to the EXPLODE function to "flatten" a collection type column into a row per element of the collection. Because Flink SQL is ANSI compliant, it’s no surprise... - Source: dev.to / 22 days ago

• Show HN: An SQS Alternative on Postgres

  You should let the Apache Flink team know, they mention exactly-once processing on their home page (under "correctness guarantees") and in their list of features. [0] https://flink.apache.org/ [1] https://flink.apache.org/what-is-flink/flink-applications/#building-blocks-for-streaming-applications. - Source: Hacker News / about 1 month ago

• Top 10 Common Data Engineers and Scientists Pain Points in 2024

  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 / 2 months ago

• Choosing Between a Streaming Database and a Stream Processing Framework in Python

  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 / 4 months ago