5 operational challenges developers face & how a message broker can overcome them

Message brokers are build upon the foundation of messaging queues, but they offer additional features and patterns. They enable not only one-to-one but also many-to-many communications. Common applications for message brokers and event streaming platforms include real-time notifications, location tracking, financial markets, and system integrations. This expanded functionality allows for many impossible use cases with traditional messaging queues.

However, there are several challenges while using message brokers. This blog dives deep into the topic based on the interview with Yaniv Ben Hemo, Co-Founder & CEO at Memphis.dev. 

The difference between a message queue & message broker

Message queues primarily facilitate one-to-one communication. They excel at enabling a single producer to send messages to a single consumer. While they can technically support more complex scenarios, they may not be as scalable for one-to-many communication, where one producer needs to notify multiple consumers.

On the other hand, message brokers are designed with greater flexibility in mind. They can support one-to-many communication patterns, where a single producer can send messages to multiple consumers. Message brokers are better equipped to handle scenarios involving high workloads, high throughputs, many events per second, and larger message sizes. A message broker is a more suitable choice in situations demanding scalability and versatility. While messaging queues have evolved to incorporate features that enable them to support more complex patterns, blurring the lines between the two technologies, message brokers remain the preferred solution when considering scalability and robust support for one-to-many communication.

Ultimately, the choice of message broker and how it handles time depends on the application’s specific use case and timing requirements. It can involve a mix of asynchronous and real-time communication, buffered or immediate message delivery, and strategies to manage the timing of message processing based on the needs of the system and the parties involved.

5 challenges with traditional message brokers 

Here are 5 challenges that developers often face when working with traditional message brokers:

1. Poor Observability: Developers often need help to understand a message broker’s interactions. It can be challenging to track who is communicating with whom, the format and size of messages, and what consumers expect to receive. Comprehensive observability tools are crucial for gaining insights into these aspects.
2. Application-Level Troubleshooting: Tracing issues and troubleshooting in complex message broker setups can be daunting. Asynchronous flows may involve multiple services and transformations, making it hard to identify the source of problems or unexpected behavior. Ensuring smooth operation and debugging across the entire chain is a significant challenge.
3. Mechanism Building: Developers must build various mechanisms to handle message broker interactions effectively. For example, in a push-based system, creating backpressure mechanisms to manage bursts of incoming messages is vital. Retry mechanisms are necessary to ensure critical messages are not lost due to processing failures.
4. Offset Recording: Keeping track of message offsets is crucial in many scenarios, especially in event streaming. Ensuring that messages are not processed twice or missed is challenging, which is essential in scenarios like order processing, shipping events, or financial transactions.
5. Repetitive Code: Large organizations with distributed teams often face the issue of writing redundant code for different services, even when they share a common messaging infrastructure. This inefficiency hampers collaboration and code reuse, as teams in various locations may implement similar logic independently.

These challenges are typical when dealing with message brokers and event streaming systems, and addressing them is crucial for ensuring such systems’ reliable and efficient operation.

Memphis.dev – A modern message broker

Memphis.dev is designed to be cloud-native, written in Go, and can run on Kubernetes across various cloud platforms. It also offers a managed version for those who prefer it. Memphis.dev can handle various challenges, including. 

1. Observability: Provides a dashboard to visualize your producers and consumers. Green icons represent active connections, helping you understand who communicates with the platform.
2. Troubleshooting: Automatically flags affected messages as ‘dead letter’ items for issues like a consumer group unexpectedly going offline. These messages are temporarily stored for you to inspect and decide whether to resend or drop them.
3. Mechanisms: Offers features like backpressure for push-based systems to manage message bursts and retry mechanisms to ensure critical messages are not lost.
4. Offset Recording: Maintains offset information, preventing messages from being processed twice or missed in event streaming scenarios.
5. Repetitive Code: Alleviates the need for redundant code across distributed teams by providing a centralized messaging solution.

How Memphis.dev addresses security concerns

One of the primary security concerns is multi-tenancy, which involves ensuring that data from one customer is never exposed to another. Memphis.dev offers multi-tenancy features that empower users to create secure separation within their internal assets and between their customers.

Authorization is another crucial security aspect, and Memphis.dev employs a role-based access approach. This contrasts traditional Access Control Lists (ACLs), which can be complex and challenging. Role-based access allows for fine-grained control over who can access data and actions within the system. It enables users to create secure roles and permissions, controlling access at various levels, from individual stations to the broader tenant level.

Lastly, compliance is a significant concern for many organizations. Memphis.dev takes steps to ensure compliance with standards and regulations. It is SOC 2 Type 1 and Type 2 compliant, and GDPR compliant, which is critical for data privacy. These measures assure organizations and customers that their data is handled securely and follows regulatory requirements.

The future of message brokers

Over the next few months to the next couple of years, a few aspects are looking to come up in this space. First and foremost, how data can be used, especially with the latest technology trends such as GPT-3, NLP models, generative AI, and more, all of these innovations are essentially derived from data. Exploring the untapped potential of existing data will be incredibly intriguing.

Message brokers are beginning to outshine traditional databases and storage systems. This domain holds immense promise and is poised for greater utilization by developers. Vendors who successfully lowers the entry barrier and attracts more developers and new audiences to the field will emerge as a leader, capturing the hearts of developers.

To know more about how Memphis.dev helps developers overcome challenges around observability and repetitive code, watch the podcast: