Texas Instruments Changes the NE5532 and Others into Incompatible Versions
Texas Instruments Changes the NE5532 and Others into Incompatible Versions
#WidespreadEnshitification #TexasInstruments #FWakeTexasInstruments
#FWakeEnshitification #NE5532 #FWakeNE5532
#OpAmp #AudioOpAmp #FWakeOpAmp
first released in year 1979 by #Signetics which was later acquired by #Philips and eventually became part of Texas Instruments...

CNCF Webinar about OpAMP
A short post, I’m excited to share that I will be presenting a Webinar for the CNCF Malaga meetup on the 11th June 6.30pm CEST where I’ll be talking about OpAMP – registration link.
I hope you can join me to hear about the value of the OpAMP protocol, which originated from the CNCF OpenTelemetry project. I’ll be talking about what the protocol can do for us, how it works, and while it has origins within the OpenTelemetry project, it has far-reaching value for almost any deployment context.
This isn’t all theory, I’ll be demoing the functionality we’ve built that leverages the OpAMP spec. While the focus will be on Fluent Bit, it will convey the value of the protocol. We’ll also look at how it can scale in both volume and the range of client applications it can support.
#agents #demo #OpAMP #OpenTelemetry #OTel #webinarFluent Bit configuration quick reference and editor
Fluent Bit’s documentation is spread across many static web pages; in some cases, attributes allowed for a plugin are documented across several pages. There is absolutely nothing wrong with this. Having written a book on Fluent Bit, I can say it makes sense, and if the standard docs went into further detail, it would increase the spread of content.
The problem is, once you’ve got a grip on Fluent Bit, you want a quick reference just to check the attribute names or confirm that an attribute does what you expect.
The good news is that’s what we have created …
Each quick reference page has a section at the top that provides a comma-separated list of all the plugins for the different operations, inputs, outputs, etc., with anchor links to that section. Each plugin has a table that lists all configuration attributes, including those inherited from the Fluent Bit kernel and those introduced by extending another plugin.
Why and how …
The “why” may prove even more appealing. As part of our OpAMP project, we wanted to make it easy to edit and validate Fluent Bit and Fluentd configurations before deployment using the OpAMP tooling. That tool became the config-service part of the OpAMP repo, and can be independently deployed as well as function as part of the main OpAMP service. As a result, the UI offers the same authentication and authorisation options, ranging from running without authentication to using OAuth.
All the different editable components collapsedPlugins part of the editorThe key to both the UI and documentation is the use of JSON Schemas, as they contain all the information needed to create documentation just as easily as they power the UI. We have therefore generated a markdown page using a Python script. This means the docs are easy to check (compared to an HTML file) and can be rendered within GitHub. We could extend the script to generate HTML. But rather than trying to remember to keep both document types in sync (and double-check formatting), we found a JavaScript tool (marked.js) that performs an on-the-fly transformation that, as long as we stay within the core Markdown syntax, won’t cause any issues. We’ve then enriched that output a bit by applying stylesheets.
To come…
At the moment, we have only covered a subset of Fluent Bit versions, so we will, in due course, expand to cover more versions. Today, this is just the last version from each major release. We haven’t done every version to date as it does take a lot of effort to go through the documentation to generate and check the schema, and we’re still refining things as we enhance the UI.
We are also looking to do the same for Fluentd, though this is much trickier, as the portfolio of plugins that make up the core is smaller than those incorporated into the core of Fluent Bit, and the leveraging of Ruby’s dynamic behaviour makes it very easy for people to offer plugins separately. Then, of course, there is the task of collating all that information.
Resources
#AI #docs #FluentBit #Fluentd #GitHub #MCP #Music #OpAMP #youtubeReduce developer friction – Configuring tools like Fluent Bit (and Fluentd)
Something that vendors like Microsoft have been really good at is reducing the friction on getting started – from simplifying installations with MSI files and defaulted options through to very informative error messages in Excel when you’ve got a function slightly wrong. Apple is another good example of this; while no two Android phones are the same, my experience is that setting up an iPhone is just so much easier than setting up an Android phone. It is also the setup/configuration where most friction comes from.
Open-Source Software (OSS), as a generalisation, tend to be a bit weaker at minimising friction – this comes from several factors:
The common challenge
The issue that I have observed is that we often go through cycles of working with a technology. For example, you’re building a microservice. Chances are, you’ll start writing and running it locally, without worrying about containerization. Once you’re pretty happy with things, you’ll Dockerize the service, start testing it locally, and then you’ll be ready to deploy it to a cluster. Now you’ll need your YAML. It may well be weeks since you last looked at Helm charts. You end up cutting and pasting your last configuration. But now you need to use another feature of Helm, can you remember the exact settings for the feature. So now you’re trawling the net for documentation, and then it takes several tries to get it right.
AI may well step in to help developers in this area, where solutions and products are well-documented. But with the wrong model or insufficient detail in the prompt, it’s easy to make a mistake. Personally, I’d turn to AI when it becomes necessary to trawl code to better understand the configuration and its behaviour, and to set options.
Experimental Solution
Solution – well, that depends upon the configuration syntax. We have been experimenting with RJSF (React JSON Schema Form), which provides a React-based UI that can be dynamically driven by a JSON schema and validate data with AJV (an alternative stack considered would have been around JSON Forms).
{ "type": "object", "title": "Dummy", "properties": { "name": { "type": "string", "const": "dummy", "title": "Plugin" }, "copies": { "type": "integer", "description": "Number of messages to generate each time messages are generated.", "x-doc-reference": "https://docs.fluentbit.io/manual/data-pipeline/inputs/dummy#configuration-parameters", "x-doc-required": false, "x-config-data-type": "integer", "default": 1 }, "dummy": { "type": "string", "description": "Dummy JSON record.", "x-doc-reference": "https://docs.fluentbit.io/manual/data-pipeline/inputs/dummy#configuration-parameters", "x-doc-required": false, "x-config-data-type": "string", "default": "{\"message\":\"dummy\"}" }, "fixed_timestamp": { "type": "boolean", "description": "If enabled, use a fixed timestamp.", "x-doc-reference": "https://docs.fluentbit.io/manual/data-pipeline/inputs/dummy#configuration-parameters", "x-doc-required": false, "x-config-data-type": "boolean", "default": false } } } The above fragment shows part of the Schema definition for the Dummy plugin for Fluent Bit.
By then creating a schema that defines the different plugins, attributes, etc., we can drive validation and menu items easily in the UI. Admittedly, the config file is significant given all the plugins and configuration options, but it is a fair price to pay for a UI that validates the data. Establishing the schema to start with, we’ve covered it through scripting the retrieval and scraping of the Fluent Bit pages, which are pretty consistent in structure.
We have added some custom elements into the definition, for example, x-doc-reference, which allows us to extend the React components to provide features such as a link back to the original documentation as you select attributes or plugins.
As a result, we very quickly have a UI that can look like this:
A lot easier to view and tweak, with no need to hunt for valid options. Even if we want more information, we’re just a button click away from the open-source data. Perhaps we should provide a version that hyperlinks to the Manning Live Books on Fluent Bit, etc.
There are a few other factors to consider; for example, Fluent Bit configuration is YAML, not JSON, which can be easily resolved given the relationship between the two standards. Then there are processors that can embed Lua code or a SQL-like syntax. As we’ve chosen to provide a Python backend, we’ve addressed this by providing REST endpoints which can query out of the JSON the code or SQL and perform validation using the Python Lua Parser, and the SQL syntax can be addressed using the Lark library for processing the SQL, as the syntax is simple enough to define and maintain the syntax.
Outstanding Gaps for Fluent Bit
We still need to address several features that Fluent Bit has, specifically:
These issues should be straightforward to overcome, although dynamically including the included elements into the UI view elements can be done. The challenge is: if any changes need to go into something that has been included, how do we push them back to the included file? Particularly if there are multiple layers of inclusion.
What about Fluentd?
Fluentd configuration isn’t JSON-based notation, but it is structured. So, to apply the same mechanism, we’ll need to define a schema and a mapping mechanism. The tricky part of the schema is that Fluentd supports nesting plugins, since the way pipelines are defined for routing differs. While JSON schema will enable this with constructs such as anyOf, oneOf, object nesting, and bounded object arrays, the structure will be more complex.
The second challenge will be the transformer/renderer, so we don’t introduce issues from having to escape and unescape characters, since JSON Schema is stricter about character use.
Then What?
Well, if we get this going, we’ll probably incorporate the capability into our OpAMP project and maybe create a build that lets the configuration tool run independently. Lastly, perhaps we should look to see if we can make the different layers a little more abstract, so we can plug in editors for other configurations, such as OTel Collectors or the ELK Stack.
As a bonus, perhaps transform the Schema into a quick reference web document?
#AI #artificialIntelligence #configuration #development #ELK #FluentBit #Fluentd #LLM #observability #OpAMP #TechnologyAnalog Circuitry Lets You Blow This LED Out
https://fed.brid.gy/r/https://hackaday.com/2026/04/21/analog-circuitry-lets-you-blow-this-led-out/
New video! Recapping the Amiga 3000T mainboard and trying to resolve the audio issues.
YouTube: https://youtu.be/HZDW2SLB47k
PeerTube: https://makertube.net/w/6tAgZ8v5kjfVGqQC1NovSD
#Amiga #Amiga3000T #Amiga3000 #A3000T #Commodore #Restoration #Audio #OpAmp #Recapping #Repair #Troubleshooting #VintageComputing #RareCommodore
OpAMP server with MCP – aka conversational Fluent Bit control
I’ve written a few times about how OpAMP (Open Agent Management Protocol) may emerge from the OpenTelemetry CNCF project, but like OTLP (OpenTelemetry Protocol), it applies to just about any observability agent, not just the OTel Collector. As a side project, giving a real-world use case work on my Python skills, as well as an excuse to work with FastMCP (and LangGraph shortly). But also to bring the evolved idea of ChatOps (see here and here).
One of the goals of ChatOps was to free us from having to actively log into specific tools to mine for information once metrics, traces, and logs reach the aggregating back ends, but being able to. If we leverage a decent LLM with Model Context Protocol tools through an app such as Claude Desktop or ChatGPT (or their mobile variants). Ideally, we have a means to free ourselves to use social collaboration tools, rather than being tied to a specific LLM toolkit.
With a UI and the ability to communicate with Fluentd and Fluent Bit without imposing changes on the agent code base (we use a supervisor model), issue commands, track what is going on, and have the option of authentication. (more improvements in this space to come).
New ChatOps – Phase 1
With the first level of the new ChatOps dynamism being through LLM desktop tooling and MCP, the following are screenshots showing how we’ve exposed part of our OpAMP server via APIs. As you can see in the screenshot within our OpAMP server, we have the concept of commands. What we have done is take some of the commands described in the OpAMP spec, call them standard commands, and then define a construct for Custom Commands (which can be dynamically added to the server and client).
The following screenshot illustrates using plain text rather than trying to come up with structured English to get the OpAMP server to shut down a Fluentd node (in this case, as we only had 1 Fluentd node, it worked out which node to stop).
Interesting considerations
What will be interesting to see is the LLM token consumption changes as the portfolio of managed agents changes, given that, to achieve the shutdown, the LLM will have had to obtain all the Fluent Bit & Fluentd instances being managed. If we provide an endpoint to find an agent instance, would the LLM reason to use that rather than trawl all the information?
Next phase
ChatGPT, Claude Desktop, and others already incorporate some level of collaboration capabilities if the users involved are on a suitable premium account (Team/Enterprise). It would be good to enable greater freedom and potentially lower costs by enabling the capability to operate through collaboration platforms such as Teams and Slack. This means the next steps need to look something along the lines of:
#AI #chatops #FluentBit #Fluentd #LangGraph #LLM #MCP #OpAMP #OpenTelemetry #OTel #OTLP