perspectives | Render shared views on the client OR on the server | Frontend Framework library

Use relative addressing

Something like this - run in full screen

Just for clarification purposes:

• Helm is a package manager with which you can install an application onto the cluster in a bundled matter: it basically provides you with all the necessary YAMLs, such as ConfigMaps, Services, Deployments, and whatever else is needed to get the desired application up and running in a proper way.

• An Operator is essentially a controller. In Kubernetes, there are lots of different controllers that define the "logic" whenever you do something (e.g. the replication-controller adds more replicates of a Pod if you decide to increment the replicas field). There simply are too many controllers to list them all and have running individually, that's why they are compiled into a single binary known as the kube-controller-manager. Custom-built controllers are called operators for easier distinction. These operators simply watch over the state of certain "things" and are going to perform an action if needed. Most of the time these "things" are going to be CustomResources (CRs) which are essentially new Kubernetes objects that were introduced to the cluster by applying CustomResourceDefinitions (CRDs).

With that being said, it is not uncommon to use helm to deploy operators, however, try to avoid the term "helm operator" as it is actually referring to a very specific operator and may lead to confusion in the future: https://github.com/fluxcd/helm-operator

So my question is, can we somehow use those helm operators inside our operator?

Although you may build your own operator with the operator-sdk which then lets you deploy or trigger certain events from other operators (e.g. by editing their CRDs) there is no reason to do so.

The only method I can think of so far is calling the helm setup console commands from within a deployment app.

Most likely what you are looking for is a proper CI/CD workflow. Simply commit the helm chart and values.yaml files that you are using during helm install inside a Git repository and have a CI/CD tool (such as GitLab) deploy them to your cluster every time you make a new commit.

Update: As the other edited his question and left a comment i decided to update this post:

The main purpose of the operator is to deploy X databases. Along with that we would like to have a single operator/bundle that deploys the whole system right away.

Do you think it makes sense to bundle operators together in another operator, as one would do with Helm?

No it does not make sense at all. That's exactly what helm is there for. With helm you can bundle stuff, you can even bundle multiple helm charts together which may be what you are actually looking for. You can have one helm chart that passes the needed values down to the actual operator helm charts and therefore use something like the service-name in multiple locations.

In the case of operators inside operators, is it still necessary to configure every sub-operator individually when configuring the operator?

As mentioned above, it does not make any sense to do it like that, it is just an over-engineered approach. However, if you truly want to go with the operator approach there are basically two approaches you could take:

• Write an operator that configures the other operators by changing their CRs, ConfigMaps etc. ; with this this approach you will have a somewhat lightweight operator, however you will have to ensure it is compatible at all times with all the different operators you want it to interfere with (when they change to a new apiVersion with breaking changes, introduce new CRs or anything of that kind, you will have to adapt again).
• Extract the entire logic from the existing operators into your operator (i.e. rebuild something that already already exists); with this approach you will have a big monolithic application that will be huge pain to maintain as you will continuously have to update your code whenever there is an update in the upstream operator

Hopefully it is clear by now that building your own operator for "operating" other operators comes with lot of painful dependencies and should not be the way to go.

Is it possible to deploy different configurations of images? Such as databases configured with different ports?

Good operators and helm charts let you do that out of the box, either via a respective CR / ConfigMap or a values.yaml file, however, that now depends on what solutions you are going to use. So in general the answer is: yes, it is possible if supported.

Show In System Explorer is defined in the org.eclipse.ui.ide plugin.xml and is controlled by this expression:

Jaeger is a distributed tracer, inspired by Google's Dapper paper, and so it is mainly used for tracing communication between different processes in a microservices / distributed system architecture, not so much for portions of code inside an application.

The way Jaeger is introduced into most applications is to integrate it into the part of the application that is receiving requests from the network. For example, if your Python application is receiving HTTP requests using Django or Flask, or other types of requests (e.g. gRPC) using some other framework, there will probably be a project somewhere on the internet that lets you hook Jaeger into your framework with a couple of lines of code. For the most popular frameworks, the Jaeger docs point to opentracing-contrib as a good source for these "client libraries".

While making extra tracing calls inside an application is not unheard of or discouraged with d.tracers, it's not something that tends to happen a lot, because d.tracers are typically used in microservices environments where the interactions between components are more important than what's happening inside the components.

If you do want to create tracing records inside an application, then it would be very unusual to do tracing of every single function. Instead, tracing inside an application would typically be done at the boundary of components in a modular monolith, i.e. when one component calls into another component.

Lastly, if what you really want is performance analysis of your single Python application at the level of each function, and you don't care about it's interaction with other applications in your system (maybe you only have the one?), then Jaeger is probably not the right tool. In that case, you would probably want to look for an Application Performance Monitoring or APM tool that works with Python and suits your needs.

tl;dr See this JSFiddle

To move from four players to six players, you have to understand the math that underlies the four player case and then apply it to the six player case.

You can think of each player's location as a given number of degrees (or radians) around a circle with an origin at the center of the table. In the four player case, the 1st player (index 0) will be at degrees 0, the 2nd player will be at 90 degrees, etc.

To determine how one player's movement affects the movement of a card on another person's screen that is not at the same angle, you need to break down the movement of the card in terms of its basis. In this case, the basis is composed of two orthogonal vectors that define the current player's movement space. The first vector is the vector generated using the angle. The second vector can be found by taking the current angle and adding 90 degrees (Pi/2 radians). For the four player case, the 1st player will have a primary basis vector of 0 degrees, which is (1,0). The 1st players secondary basis vector will be 0+90=90 degrees, which is (0,1).

To translate the mouse movement (delta screen x and y) into movement using an arbitrary basis, you take the dot product of delta screen x and y and the x and y of each vector in the basis. In the four player case, when the 1st player moves a card, the dot product of the primary and secondary basis result in the x delta and the y delta, respectively.

After you calculate this for the current player, you can to move the cards on other player's screens in terms of their basis. To do this, take the movement that has been converted into movement along the two bases and apply it to each other player's basis. In the four player case, the 2nd player's primary basis is 90 degrees = (1,0) and the secondary basis is 90+90 degrees = (-1,0). Thus to mirror the movement at the 2nd player's position, the original x movement is converted to y movement and the original y movement is converted to -x movement.

To change this to a game with an arbitrary number of players and with a potential offset from 0 degrees for the 1st player, you need to follow the same math. First, calculate the bases for each player. Second, use dot products to calculate the delta of the card being movement in terms of its basis. Third, apply this movement to the bases of the other players.

The example below lets you change the number of players and the starting offset angle. The cards are divs and there is a canvas superimposed over the divs to show the primary axes (red) and the secondary axes (blue) for each basis.

Ok I solved my problem with the css below, if someone finds better, let me know:

The "Legacy" means the "SQL Server reporting" feature is the old preferred way for reporting.

Now, the new preferred way recommended for reporting is "Analytics service" feature with "Power BI integration", and currently this feature is in "Preview". More details, you can see "Analytics & Power BI integration (Preview)".

And please also reference to "Reporting roadmap for Azure DevOps".

You can choose any one of the two ways to generate reporting in your Azure DevOps Server 2019. This depends on which way you and your company prefer to use.

What your are trying to achieve is easier to implement with the css rotate3d function.

You can mimic the rotation of an inclined element by just using transform: rotate3d(-0.3, 1, 0, 390deg):

Be sure that the z-index is effective. Remember that it only applies on positioned elements, which mean that if your background-image and div do not have a "position" attribute it will not take the z-index into consideration.