OpenTracing is a largely ignored variant of the more popular distributed tracing technique, commonly used in microservice architectures. Users may be familiar with the culture of using distributed tracing for profiling and monitoring applications. For the newcomers, here’s a better way of understanding what OpenTracing does. Think of an open-ended tool that can connect you with the specifications of an API using frameworks, documentation and libraries for a given project.
Now imagine adding all the necessary code and instrumentation to such a project without shifting from one product or vendor to the next. Built as a tool to connect users and coders with a singular engine to perform operations beyond distributed tracing, OpenTracing debuting a few years back and is currently incubated under the Cloud Native Computing Foundation. Let’s take a more succinct look at what makes it so unique.
What Is Distributed Tracing & Why Do We Use It?
Distributed tracing works as an effective mechanism to track a single request sent by the system unlike conventional forms of tracing requests that move through a single application domain. To be clearer, distributed tracing helps in connecting multiple requests across multiple platforms or systems. This ‘tracing’ or coagulated streaming is done by creating a sequence of correlation IDs(for the streams) and storing log events as the steam moves through multiple systems.
In this way, distributed tracing helps locate the points in a system where failures can occur and remove elements from the network that may lead to reduced performance. Of course, it should be noted that users can only move on to the process of profiling streams and looking for points of failure, only once the code has been productionized and moved to the mainframe. But is there a way to bypass this entire requirement?
The Opulence of OpenTracing: Why It Matters
Let’s get a few facts clear first. OpenTracing doesn’t position itself as a downloadable platform of program. It also isn’t a standard that’s used by the industry. Despite still being in incubation in the Cloud Native Computing Foundation(CNCF), its merits should not be overlooked. If distributed tracing is the precursor to the age of the microservices, OpenTracing may just be the next big thing.
The concept of tracing itself is seen as integral to important operations such as anomaly detection, predictive maintenance, studying steady state systems in the industry, profiling, resource attribution and modelling microservices. OpenTracing is thus best described as a more defined method to debug and study complex networks, for the simple reason that it employs no in-memory calls or stack traces to do so.
Telemetry & How OpenTracing Achieves What It Should
Telemetry is a tough trade in the industry. Data collection and analysis requires a keen eye that has to consider multiple facets including safety, security, access control, space and so on. OpenTracing, as an industry method, utilizes a vendor-agnostic API system to help developers easily study the nooks and crannies of their code. This is where another important facet appears- ‘openness’. Since no company owns the methodology, it remains a standardized way to instrument tracing.
Think of a trace as the image or record of data that engineers and coders use in telemetry. OpenTracing intends to create a singular language around what a trace is and how to best document it. OpenTracing defines a trace as a directed acyclic graph, composed of spans(similar to a span of rows and columns in Excel) and references.
The OpenTracing API runs similar to a tool filled with elements called traces where users can keep a close watch on systems, while maintaining a vendor neutral framework for instrumentation. By neutrality, this means that if a user had to apply the same distributed system to a new project or system, all that would have to be changed is the configuration of the tracer. Let’s take a more concise element at important elements used in OpenTracing.
OpenTracing Elements: Most Important Tools To Know
A gateway for entering the tracing API, that allows users to create Spans and other important data tracing elements for the system. The tracer also works as a method for extracting information about the data record and insert information/data to the different networks in the node.
The span can be best regarded as a unit of work in the actual trace i.e., major operation or project. There are different types of spans depending on the data being examined or traced, and the data source. A trace created using a web based application is referred to as a root Span.
If this span is combined with another web application, the new trace would be inserted thus as part of a new child Span. Spans essentially contain metadata about the data being traced, including tags related to the information related to the data.
Logs can be created within the context of spans and drafted to record additional record about the data. Logs can be used to support more complex workflows than web requests, such as asynchronous messaging. Logs can also be inserted along with messages that contain timestamps, helping users understand the chronology of the events and data being examined through a trace.
The SpanContext is a serialized subset of an existing span. It is best used for the transfer of data slices(fragments of an existing trace or dataset) from a wire or node to other systems. Certain methods are used to create spans and spancontexts for data that is generated in real time, such as in manufacturing stations.
What Makes OpenTracing Unique
Apart from the ease with which users can pick up the OpenTracing system and apply it with a series of simple commands, using it is absolutely cathartic. Learning about the commands and mastering is also far easier compared to its counterparts, as the system enjoys a fairly standard learning curve. Unlike other systems that are open source, OpenTracing maintains a popular user base that has been able to legitimize it with documentations and constant stackoverflow fixes.
Here are some other unique advantages that makes it amazing:-
- Composed of a simple array of tools that are partially inspired by previous tracing mechanisms, OpenTracing is well suited for applications for all sizes and types.
- Communicating data changes and spans is well designed and can be made with no complications.
- Multipurpose compatibility helps OpenTracing to be inserted into all forms of data and all types of data sources, no matter how obscure or complex. If the data can be tabulated or converted to a series, OpenTracing will work.
- Users can apply telemetry operations and edits to code without the need to wait for deployment or wait for applications to return errors. This makes it a great addition to the current culture of agile software development.
Some Good Practices To Remember When Running OpenTracing
Based on comments from the community, let’s keep some good practices in check:-
- Utilize dependency injection where you can so that tracers can be inserted easily and tests can be perfectly added for productionizing code. possible.
- OpenTracing should be restricted from the business aspect of data collection and telemetry, given certain contention in the past regarding safety and data security. If the project you have can’t use any extensibility points, keep most of the tracing instrumentation restricted as possible.
- Use existing industry standards like Decorator and Chain of Responsibility. It makes the code easier to be interpreted and transferred to others.
- Use a well defined language and framework. OpenTracing allows users to be as independent as they want to be with syntax and structure, in order to remove the complications of data collection and tracing.
Off The Record: Where OpenTracing Fails
Before we get to part where a newcomer gets bashed straight to oblivion, let’s make something clear. OpenTracing is somewhat of an industry standard that enjoys a lot of support from telemetry enthusiasts and coders. It is this open source nature that made it easy to pick up and adopt across multiple languages and codebases.
But certain facts must also be acknowledged. OpenTracing is also seen as a deprecated specification and has always had the ‘end of life’ knife hanging above its head. The open source nature also has brought up criticisms for being vulnerable to data leaks and attacks(which for the most part seems unavoidable in the data realm). The demerits of applying telemetry operations on real time data, has also been a contentious subject. But since the OpenTracing system remains far from being licensed or standardized to the same levels as a system like Python, it is most likely to be replaced with a new contender.
OpenTracing is close to reaching its end of life agreements and may suffer from infrequent updates if it doesn’t become too popular.
Final Words & The Road Ahead
Those well versed with tracing would be aware that more and more projects are beginning to make a transition to OpenTelemetry as OpenTracing is thrown to the sidelines in the next few years. This should not discount the achievements that OpenTracing has helped users reach. The system has become a foundation for seamless tracing and data examination, while providing the building blocks for its eventual successors.
Newcomers shouldn’t feel discouraged and still stroll through OpenTracing. The best ways are again by looking at documentations, tutorials and taking a swing at using OpenTracing at their own projects. For all intents and purposes, it still packs a lot of punch. Tune in next time, as we explore other tools and methods, for the developer/coder in all of you.
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