Zabbix Reviews

1. Stan

   | Founder at SaaSHub | about 1 year ago
   Indispensable

   Zabbix has been part of my toolbox for quite some time. I can easily say it's an indispensable tool for me now.

   Managing a dozen servers without Zabbix would be unimaginable. I'm monitoring all of this: CPU, Memory, Hard-drives, website response times, downtime. The UI might be a bit "old school", but everything works flawlessly.

   With regards to hard-drive monitoring, I love the machine learning option that allows you to "predict" the number of days before running out of space. That's quite helpful, as I've got some of my servers down due to running out of space multiple times in the past (before I was using Zabbix).

   👍 Pros:    Open-source|It can monitor everything

   👎 Cons:    The ui is a bit unintuitive in some cases

Apache Flink Reviews

Zabbix mentions (5)

• Learning Resources

  Official Zabbix trainings, documentation on zabbix.com ? Source: over 1 year ago

• zabbix installation

  Hallo, do you know a howto to install zabbix on an ubuntu 20.04 ? I tried the manuals from zabbix.com for MySQL Apache but it didn't work. Source: about 2 years ago

• How I am getting experience as a linux admistrator (Follow Up)

  He suggested that I indeed should set up a home-lab. To be specific he said that I should create a minimal install of Centos 8 and install zabbix server on it (https://zabbix.com) and monitor a whole bunch of other VMs, services and stuff.. He said that I should set up a variety of VMs and also maybe host a website on one of them. And then if I was able to do that, I could help to share a load of zabbix related... Source: over 2 years ago

• Ubuntu Impish 21.10 / Zabbix 6.0 LTS

  This is a fresh 21.10 install, using the install repo as detailed on the zabbix.com download page. Source: over 2 years ago

• One dev conference speaker's family member died, need your help to fill the speaking slot on Nov 27/28

  Well, if you can't find anyone, I am more than happy to fill the slot with something regarding Zabbix - just let me know ;). Source: over 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 / 14 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 / about 1 month 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 2 months 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 / 3 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 / 5 months ago