VISUALIZING TRAFFIC SAFETY WITH UBER MOVEMENT DATA AND KEPLER.GL
Learn how to use Kepler.gl for data visualization through our tutorial, where we show how easy it is to load multiple datasets into Kepler.gl to visualize traffic safety in Manhattan. Urban traffic can be dangerous, a point known all too well by city dwellers and drivers. Discovering the most dangerous street locations in a city can help urban planners take steps to enhance safety through strategies such as lower speed limits or traffic rerouting.
Read moreHELM 3 ALPHA RELEASE AVAILABLE AND WHAT’S NEXT
On October 15th, 2015, the project now known as Helm was born. Only one year later, the Helm community joined the Kubernetes organization as Helm 2 was fast approaching. In June 2018, the Helm community joined the CNCF as an incubating project. Fast forward to today, and Helm 3 is nearing its first alpha release. Helm 1 began as an open source project created by Deis. We were a small startup company acquired by Microsoft in the spring of 2017.
Read moreAWS APP MESH—SERVICE MESH FOR MICROSERVICES RUNNING ON AWS
The idea of a “service mesh” has become increasingly popular over the last couple of years and the number of alternatives available has risen. There are multiple service mesh open-source projects: Istio, Linkerd, Envoy and Conduit which can be deployed on any Kubernetes environment. The AWS App Mesh can be used with microservices running on Amazon Elastic Container Service (Amazon ECS), Amazon Elastic Container Service for Kubernetes (Amazon EKS), and Kubernetes running on Amazon EC2.
Read moreAWS APP MESH IS NOW GENERALLY AVAILABLE
AWS App Mesh is now generally available and supported for production use. App Mesh is a service mesh that provides application level networking to make it easy for your services to communicate with each other across multiple types of compute infrastructure. App Mesh standardizes how your services communicate, giving you end-to-end visibility and ensuring high-availability for your applications. Modern applications are typically composed of multiple services. Each service may be built using multiple types of compute infrastructure such as Amazon EC2 and AWS Fargate. As the number of services grow within an application, it becomes difficult to pinpoint the exact location of errors, re-route traffic after failures, and safely deploy code changes.
Read moreFROM MONOLITH TO MICROSERVICES
To tackle this monolith, we initially began exploring how the codebase was built. It had a high level of complexity with too many features baked into the all-in-one code, as well as thousands of unit tests. Without consistent APIs, many nonstandard integrations, or one-offs, had been deployed. Tight coupling of integrations existed at every level, including on modules and datastores, without boundaries. For functional test cases, quality took a big hit. Lot of gaps were present and band-aid fixes often led to further quality issues.
Read moreHOW MUCH RAM DOES PROMETHEUS 2.X NEED FOR CARDINALITY AND INGESTION?
Prometheus 2.x has a very different ingestion system to 1.x, with many performance improvements. This time I’m also going to take into account the cost of cardinality in the head block. To start with I took a profile of a Prometheus 2.9.2 ingesting from a single target with 100k unique time series: This gives a good starting point to find the relevant bits of code, but as my Prometheus has just started doesn’t have quite everything.
Read moreAMAZON S3 PATH DEPRECATION PLAN
Last week we made a fairly quiet (too quiet, in fact) announcement of our plan to slowly and carefully deprecate the path-based access model that is used to specify the address of an object in an S3 bucket. I spent some time talking to the S3 team in order to get a better understanding of the plan. We launched S3 in early 2006. Jeff Bezos’ original spec for S3 was very succinct – he wanted malloc (a key memory allocation function for C programs) for the Internet. From that starting point, S3 has grown to the point where it now stores many trillions of objects and processes millions of requests per second for them. Over the intervening 13 years, we have added many new storage options, features, and security controls to S3.
Read moreROOK V1.0, A MAJOR MILESTONE
The Rook project, as well as its thriving community, has continued to grow and evolve since the initial public release in November 2016. As the code base has matured through a series of minor releases, starting with the humble beginnings of v0.1 and reaching v0.9 late last year, we are incredibly pleased to finally announce the first major release of Rook, version 1.0! We will dive into some of the exciting new features included in this release, but let’s start with a community stats update first.
Read moreCILIUM USER SURVEY MARCH 2019
The survey was announced on our Slack channel and on Twitter. Participation was anonymous and did not require to leave behind contact information. Most questions had a set of predefined answers plus a field to add additional answers. All questions were optional, some users did not answer all questions. Source: cilium.io
HOW TO RUN OPENWHISK ACTIONS ON KNATIVE?
It’s now time to show case what it takes to run an existing OpenWhisk action on Knative. Matt Rutkowski and I are very excited to share our process of building and serving OpenWhisk actions on Knative here. We started prototyping OpenWhisk NodeJS Runtime with a hello world action. Later, extended the runtime to handle more complex use cases such as: It’s a six step process, first three steps are one time deployment per Knative installation. The whole build and serve process is based on Knative Source-to-URL workflow. Knative needs access to your container registry in order to push locally built container image.
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