Announcing the Community Ansible 3.0.0 Package

Version 3.0.0 of the Ansible community package marks the end of the restructuring of the Ansible ecosystem. This work culminates what began in 2019 to restructure the Ansible project and shape how Ansible content was delivered. Starting with Ansible 3.0.0, the versioning and naming reflects the new structure of the project in the following ways: 

  1. The versioning methodology for the Ansible community package now adopts semantic versioning, and begins to diverge from the versions of the Ansible Core package (which contains the Ansible language and runtime)
  2. The forthcoming Ansible Core package will be renamed from ansible-base in version 2.10 to ansible-core in version 2.11 for consistency

First, a little history. In Ansible 2.9 and prior, every plugin and module was in the Ansible project (https://github.com/ansible/ansible) itself. When you installed the "ansible" package, you got the language, runtime, and all content (modules and other plugins). Over time, the overwhelming popularity of Ansible created scalability concerns. Users had to wait many months for updated content. Developers had to rely on Ansible maintainers to review and merge their content. These obvious bottlenecks needed to be addressed. 

During the Ansible 2.10 development Continue reading

Red Hat Ansible Automation Platform Product Status Update

The Red Hat Ansible Product Team wanted to provide an update on the status and progress of Ansible’s foundational role as it pertains to the product, specifically as a deliverable for implementing automation as a language. That is, Ansible as provided by aggregated low-level command line binary executables leveraging Python, with a YAML-based user abstraction. Specifically, the packaged deliverable is currently named Ansible Base, but will soon be named Ansible Core later this year. When people often generally refer to “Ansible,” this largely describes what people use directly as part of their day-to-day development efforts.

As an Ansible Automation Platform user, you may have noticed changes over the last year and a half to the Ansible open source project and downstream product in order to provide targeted solutions for each customer persona, focusing on enhancements to packaging, release cadence, and content development.

We’ve seen the community and enterprise user bases of Ansible continue to grow as different groups adopt Ansible due to its strengths and its ability to automate a broad set of IT domains (such as Linux, Windows, network, cloud, security, storage, etc.).  But with this success it became apparent that there is no one size Continue reading

Ansible 3.0.0 Q&A

The Ansible community team has announced the release of Ansible 3.0.0 and here are the questions about the release that we’ve heard from community members so far. If you have a question that is not answered below, let us know on the mailing lists or IRC.

  • How can I stay up to date with changes in the Ansible community?

About the Ansible community package and ansible-base/ansible-core

  • Are there any changes to the Ansible language in 3.0.0?
  • There are no significant changes since the Ansible 3.0.0 package depends on the same version of ansible-base as Ansible 2.10.x.
  • Why are the versions of ansible-base/ansible-core packages diverging from the Ansible package?
    • When the Ansible Community Team set out to restructure the Ansible project, Ansible was split into the following components: 
      • The core engine, modules and plugins
      • Community and partner supported Ansible Collections of modules and plugins

The former became known as Continue reading

Data Model Transformations in Network Automation Solutions

Last year I wrote an article describing data model optimization going from a simple this is what we need to configure individual devices to a highly polished high-level network nodes and links model. Not surprisingly, as Jeremy Schulman was quick to point out, the latter one had Jinja2 templates you wouldn’t want to debug. Ever. You can’t run away from complexity… but you can manage it.

Many successful network automation solutions (example: Cisco NSO) solve the “we’d love to work with high-level data models but hate complex templates” challenge with data transformation: operators work with an abstracted data model describing services, nodes and links, and the device configuration templates use low-level data derived from the abstracted data models through a series of business logic rules or lookups (aka network design).

Read more …

Data Model Transformations in Network Automation Solutions

Last year I wrote an article describing data model optimization going from a simple this is what we need to configure individual devices to a highly polished high-level network nodes and links model. Not surprisingly, as Jeremy Schulman was quick to point out, the latter one had Jinja2 templates you wouldn’t want to debug. Ever. You can’t run away from complexity… but you can manage it.

Many successful network automation solutions (example: Cisco NSO) solve the “we’d love to work with high-level data models but hate complex templates” challenge with data transformation: operators work with an abstracted data model describing services, nodes and links, and the device configuration templates use low-level data derived from the abstracted data models through a series of business logic rules or lookups (aka network design).

Read more …

Cisco, AWS integrate IoT, edge network software and services

Cisco continues to expand customer cloud-neutral connectivity options, this time tying its Edge Intelligence software with Amazon Web Services' IoT cloud service.Specifically, Cisco’s Edge Intelligence software now works with AWS’s IOT Core service to let customers process data from, communicate with and manage thousands of IoT devices and applications linked via industrial operations networks.Cisco Edge Intelligence runs on Cisco's IoT and industrial networking family and gathers data from connected devices to create logical flows from the edge into private, public or third-party clouds. For example, if a robotic arm in a remote system needs replacement, it can send telemetry about the problem. Edge Intelligence extracts that data and gives the operational-technology team information it can use to fix the problem.To read this article in full, please click here

Cisco, AWS integrate IoT, edge network software and services

Cisco continues to expand customer cloud-neutral connectivity options, this time tying its Edge Intelligence software with Amazon Web Services' IoT cloud service.Specifically, Cisco’s Edge Intelligence software now works with AWS’s IOT Core service to let customers process data from, communicate with and manage thousands of IoT devices and applications linked via industrial operations networks.Cisco Edge Intelligence runs on Cisco's IoT and industrial networking family and gathers data from connected devices to create logical flows from the edge into private, public or third-party clouds. For example, if a robotic arm in a remote system needs replacement, it can send telemetry about the problem. Edge Intelligence extracts that data and gives the operational-technology team information it can use to fix the problem.To read this article in full, please click here

Cisco, AWS integrate IoT, edge network software and serivces

Cisco continues to expand customer cloud-neutral connectivity options, this time tying its Edge Intelligence software with Amazon Web Services' IoT cloud service.Specifically, Cisco’s Edge Intelligence software now works with AWS’s IOT Core service to let customers process data from, communicate with and manage thousands of IoT devices and applications linked via industrial operations networks.Cisco Edge Intelligence runs on Cisco’s IoT and industrial networking family and gathers data from connected devices to create logical flows from the edge into private, public or third-party clouds. For example, if a robotic arm in a remote system needs replacement, it can send telemetry about the problem. Edge Intelligence extracts that data and gives the operational-technology team information it can use to fix the problem.To read this article in full, please click here

Cisco, AWS integrate IoT, edge network software and serivces

Cisco continues to expand customer cloud-neutral connectivity options, this time tying its Edge Intelligence software with Amazon Web Services' IoT cloud service.Specifically, Cisco’s Edge Intelligence software now works with AWS’s IOT Core service to let customers process data from, communicate with and manage thousands of IoT devices and applications linked via industrial operations networks.Cisco Edge Intelligence runs on Cisco’s IoT and industrial networking family and gathers data from connected devices to create logical flows from the edge into private, public or third-party clouds. For example, if a robotic arm in a remote system needs replacement, it can send telemetry about the problem. Edge Intelligence extracts that data and gives the operational-technology team information it can use to fix the problem.To read this article in full, please click here

Internet Shutdowns: How to Undermine Trust in the Network of Networks

The Indian government’s recent Internet shutdown during farmer protests impacted over 50 million residents. It is a stark warning of the danger of tampering with the foundations that make the Internet work for everyone.

Internet shutdowns are a dangerous tactic increasingly used by the state to quell situations of unrest. In this instance, it occurred during protests in the capital, Delhi, where farmers are asking for a repeal of three state-proposed farm laws. But while the initial Internet shutdown was targeted in Delhi and lasted around 29 hours, it soon extended to districts in the neighboring state of Haryana from 26 January to 1 February to “prevent disturbance to peace and public order”.

The consequence of shutting down parts of the Internet to prevent citizen access is profound: it undermines the global Internet infrastructure, which is based on collaboration and trust, and has severe individual and economic consequences that can extend far beyond a nation’s borders.

The Internet is an incredibly successful and powerful tool, a fact that has become all too clear during the COVID-19 pandemic. It is a key technology for supporting education, economic activity, and even access to healthcare for those under stay-at-home orders. Continue reading

The Three Levels of Data Protection for Data Hoarders

The following post is aimed for photographers and other digital hoarders. Those of us that want to keep various digital assets not just for a few years, but a lifetime, and even multiple lifetimes (passed down, etc.)

There are three levels of data protection: Data resiliency, data backup, and data archive.

Data Resiliency (Redundant Disks, RAID, NAS/DAS)

Data resiliency is when you have multiple disks in some sort of redundant configuration. Typically this is some type of RAID array, through there are other technologies now that operate similar to RAID (such as ZFS, Storage Spaces, etc.) This will protect you from a drive failure. It will not, however, protect you from accidental file deletion, theft, flood/natural disaster, etc. The drives have the same file system on them, and thus have a lot of “shared fate”, where if something happens to one, it can happen to the other.

To put it simply, while there are some scenarios where your data is protected by data resiliency (drive failure), there are scenarios where it won’t (flood, theft).

RAID is not backup.

Data Backup

One of the maxims we have in the IT industry in which I’ve worked for the past Continue reading

Preempting Gray Failures With AI/ML

The network was definitely up, and had been up. There was nothing in the logs indicating link flaps, spanning-tree convergence events, or routing process adjacency changes. The packets had been, were presently, and presumably would forever be flowing. Flowing like a river. I was pondering this inaccurate version of reality because of an annoying ticket that wouldn’t go away...

The post Preempting Gray Failures With AI/ML appeared first on Packet Pushers.

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Benchmark (YCSB) numbers for Redis, MongoDB, Couchbase2, Yugabyte and BangDB

This is guest post by Sachin Sinha who is passionate about data, analytics and machine learning at scale. Author & founder of BangDB.

This article is to simply report the YCSB bench test results in detail for five NoSQL databases namely Redis, MongoDB, Couchbase, Yugabyte and BangDB and compare the result side by side. I have used latest versions for each NoSQL DB and have followed the recommendations to run all the databases in optimized conditions. I have also used the default six test scenarios as defined by the YCSB framework. I have restricted it to 10M records for each test. However, user can run the bench for as many numbers as they practically find suitable.

About YCSB

Following configurations were used for the evaluation purpose.

Each of these workload test runs in two steps, 1. Load and 2. Run. Load stage is to load the data and then run stage we run the test. I have run each test with Continue reading

Day Two Cloud 085: Hosting Your Infrastructure Code In The Cloud

Let’s say I host my Infrastructure as Code provisioning stuff locally. It works. It’s nearby. I feel in control. Are there good reasons I should move that stuff to the cloud? Here to help us sort the pros and cons of that question is Calvin Hendryx-Parker. Calvin is the co-founder and CTO of Six Feet Up, a Python web application development company.

The post Day Two Cloud 085: Hosting Your Infrastructure Code In The Cloud appeared first on Packet Pushers.

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