Response: Global Internet Map Map 2021
Bandwidth map of global internet
Bandwidth map of global internet
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).
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).
Why the Fortune 500 is (Just) Finally Dumping Hadoop
Remember how, just a decade ago, Hadoop was the cure to all the world’s large-scale enterprise IT problems? …
Why the Fortune 500 is (Just) Finally Dumping Hadoop was written by Nicole Hemsoth at The Next Platform.
Finally, Internet…and Then There Were 10,000
Eric Rux takes a deep dive into Starlink: Broadband Internet for remote and rural areas.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.
- Redis Server: 5.07, x86/64
- MongoDB server: 4.4.2, x86_64
- YugabyteDB:2.5.0, x86_64
- Couchbase2: 7.0 Beta, x86_64
- BangDB server: 2.0.0, x86_64
- Number of records: 10M
- RAM: 32GB, Cores: 16
- YCSB workloads: see github.com/brianfrankcooper/YCSB/wiki/Core-Workloads
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
The Citadel That Is Still Cisco Systems
The hyperscalers and cloud builders can be split into two camps, but a third one might be emerging. …
The Citadel That Is Still Cisco Systems was written by Timothy Prickett Morgan at The Next Platform.
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.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.
New Docker Desktop Preview for Apple M1 Released
This is just a quick update to let you know that we’ve released another preview of Docker Desktop for Apple M1 chips, which you can download from our Docker Apple M1 Tech Preview page. The most exciting change in this version is that Kubernetes now works.
First, a big thank you to everyone who tried out the previous preview and gave us feedback. We’re really excited to see how much enthusiasm there is for this, and also really grateful to you for reporting what doesn’t yet work and what your highest priorities are for quick fixes. In this post, we want to update you on what we’ve done and what we’re still working on.
Some of the biggest things we’ve been doing since the New Year are not immediately visible but are an essential part of eventually turning this into a supported product. The previous preview was built on a developer’s laptop from a private branch. Now all of the code is fully integrated into our main development branch. We’ve extended our CI suite to add several M1 machines, and we’ve extended our CI code to build and test Docker Desktop itself and all our dependencies for both architectures in Continue reading