Choosing the right database platform for your IoT system is challenging. There are a lot of considerations you need to make before settling on an option. These include flexibility, location of the database, high availability, scalability, and fault tolerance.
Before settling for a database platform, assess the data types and data flow. Don’t forget to define their functional performance and your business requirements.
Is Database Testing Necessary?
Yes, it is. You want to settle for a database that’s compatible with your IoT system. Testing helps you make the right choice. It ensures the data values and information received in the database are accurate.
Database testing can be manual, automated, or a mixture of both. Nonetheless, manual testing should be limited because of the flaws that come with human error. Instead, organizations and individuals should embrace test automation as it helps ensure accuracy and efficiency.
Although both tests can be performed under the same department by the same person, not everybody is good with automated tests. Testers need to be good at automated testing to make sure that the tests are carried out accurately.
There are a lot of materials dedicated to automated testing for beginners. The materials help beginner testers start their journey on automated testing. They will learn everything about being an automated developer. Also, they’ll learn aspects like development ecosystem, unit testing framework, DevOps, and test automation structure.
Importance of Test Automation in IoT Applications
Automation is one of the crucial components of IoT. It has resulted in the testing strategies and methods being more accurate to ensure it performs flawlessly. As technology continues to evolve, there’s a need to build effective, robust apps.
The primary goal of automation testing in IoT applications is to plan and promote a standard industry framework for fast software delivery.
It’s also one of the most lightweight approaches to IoT development. It ensures:
- Real-time data accuracy.
- Expansion of applications locally or through the internet.
- Access control through decryption and encryption.
- The IoT application supports multi-users and can be set in a dispersed environment.
- Proper data validation occurs throughout the application.
- The active applications have a good response time.
Most testing methods are being designed to make the most out of automation. Now more than ever, the need for automation testing has become more crucial.
Here are some benefits of IoT testing:
- Better engagement – It ensures end-users enjoy a top-notch user experience in multiple channels. These include the web and mobile devices.
- Speedy time to market – IoT testing leverages early automation, thus ensuring a faster marketing time.
- Contributes to the future perspective about business – IoT offers a combined approach to validate the non-functional and functional needs of the IoT solution. It modernizes the business by ensuring performance, security testing, and compatibility.
Test Automation – Crucial Points
The world is starting to lean heavily on data. It has become essential to manage vast amounts of data that can be efficiently processed and utilized for testing purposes.
Moreover, data companies require massive infrastructure to analyze such data. This becomes a task of its own when proper automation techniques are not set in place. The below points define how easy life can get when automation testing is enabled.
- As the industry is aware, not all testing methodologies are suitable for IoT elements. This renders some testing methods practically useless but, at the same time, increases the need for automation testing.
- Use resources to simply check whether systems are in place rather than working on a fix or even kick-starting the application.
- IoT performance will soon become the benchmark for cutting-edge tech companies, leading to various management problems that can be solved by automation testing.
- Automation testing sets a standard for organizations to look up to. A company that offers an excellent framework for IoT applications becomes the king of the hill.
- The methods involve user involvement, market value, integrated testing, and delivery methodologies. This is why it becomes an invaluable tool with agile software delivery incorporated in it.
Some fundamental issues involved in IoT application development can become ecosystem-level problems. With the proper IT Services, you can make a difference to your IoT applications. The methods listed above make it easy to test, roll out applications, and update in real-time with expected accuracy.
The usage of such fluid methodologies greatly improves the response time of the applications. However, doing a feasibility study is recommended to ensure greater adaptability.
Now let’s get into the 4 steps to follow when choosing a suitable database for your IoT system.
1. Identify the Data Needs for Your IoT Solution
A complete IoT solution is a complex concept. It involves collecting and processing data from connected devices to enable specific actions.
It also involves making smart decisions on triggering notifications, gleaning patterns from the historical data, and real-time computing analytics. An IoT solution may have actuators and sensors that are installed across the device.
Before settling for a data system, ask yourself the following questions.
- What is the topology of the servers? – these include its configuration and available storage, and RAM.
- What are decision-making and data processing tasks delegated to the edge servers?
- How wide is the cloud solution deployed? Is it in one region or across multiple places?
- How long does it take to respond to any critical event?
- Does the IoT solution control the actuators?
- What is the business insight you want to get from historical data?
2. Break Down Your Solutions to Independent Software Services
The second step involves analyzing the software or components that perform independent specific tasks. Here are some of these components.
Data Ingest
It collects and stores all logs and messages from the devices. It should support high-speed write operations. It also needs to ensure that all data is captured and doesn’t disappear under any circumstances.
Device Manager
The device manager communicates messages across different platforms. These messages act as control signals. The database should access the messages and deliver them at maximum speed and minimum latency.
Edge Analytics
This server performs classification, data translation, aggregation, and functioning of the incoming data. Your databases should support high read and provide tools to perform complex analytical computations.
Command and Control Dashboard
The command and control dashboard delivers the visual representation of the IoT system in its current state. The database thus needs to maintain accurate data that’s up to date. It should also read it with minimal latency.
Business Intelligence
Businesses intelligence runs inferences, reports, and queries from the historical data. The database needs to store the information for a longer time and be cost-effective. It should provide the tools to query and analyze the data.
3. Group Your Services by Their Data Needs
After breaking down your system, it’s time to choose the proper database(s) based on the data of each service. Databases can be grouped into two major types: the hot database and the cold database.
Hot database
Hot data is the data you frequently access and transfer to a given system. With the cost of RAM getting affordable, an in-memory database is an excellent choice. The in-memory database delivers data write and read capabilities using minimal latency.
The following are considerations of qualifications you should make when settling for a hot database.
Flexibility
Flexibility with data formats is essential if you want to support multiple devices. Flexibility allows you to keep data and communication formats.
Messaging and Queueing
Strong messaging and queuing solutions ensure all the services are connected across different geographical locations. A database that supports multiple streams helps in queuing and messaging. Also, it helps with data filtering, analysis, and data transformation in real-time.
Binary Safe
IoT solutions usually store binary data. An example is videos from CCTVs. Check if your system needs accessing or storing binary data. If it does, opt for a database that’s binary data safe.
Geo Distribution
If your IoT network is geographically distributed, the architecture may require some services to stay close to your devices. Thus, you need a database that supports geo-distribution.
Data Spillover and Scaling
IoT solution data often grows rapidly. Thus, when designing the capacity for hot storage, have a plan on what to do when the RAM is full. Check if the high-speed database has ‘tiered’ memory access. Here, the disk or flash memory can be used as a RAM extender.
Cold Database
Cold is the data that’s infrequently accessed. The historical data for IoT can grow to multiple terabytes. Hence, the storage solutions on the commodity are amongst the most common places to store historical information.
If you are storing your data with the cloud, check with the cloud provider to help you in determining the best storage solution in your region.
4. Evaluate the Cost and Resource Efficiency
With several database options in existence, you want to go for one that’s affordable and serves your needs. For instance, a high data database can satisfy all the requirements for a host database. For a cold database, some great options include relational databases to data lakes.
The total cost of owning a database varies depending on different factors. The cost of the database is only a tiny portion of the total expenses. Most expenses associated with owning a database include the cost of computing, operational overhead, networking, and storage resources.
Also, evaluate the cost of the data loss and the possibility that it might occur.
IoT Edge Computing and Real-Time Decision Making
Edge computing is computing that takes place near or at a physical location of a user or source of data. When you place these computing services closer to these locations, users get reliable services and a better user experience.
It involves elements like performance, latency, and security advantages of a company’s IT. The result is lower latency and saving of bandwidth. Edge computing is compatible with technology like 5G, hybrid cloud, IoT applications, and other devices.
An IoT system works by sending, receiving, and analyzing data. Edge computing enables you to benefit from the massive amount of data created by connected IoT devices. It does this through machine learning models and analytics algorithm models.
The edge data processing happens locally hence can be used for fast decision making. Companies continue using IoT in the management of industrial applications. Edge computing, therefore, helps them gain more real-time analytics to assist them in faster decision-making.
They benefit by managing to support latency-sensitive applications. By using technology like AI/ML analysis they identify trends and offer better services and products.
Companies can also use edge computing to distribute a shared pool of resources across a wide range of locations. This helps them scale centralized infrastructure to meet the needs of an increasing number of devices and data.
Without edge computing, IoT would rely on computer services and network connectivity from the datacentre or cloud. Unfortunately, sending data between IoT and cloud could result in operational efficiency and low response time.
Edge computing helps address network bandwidth needed to send massive amounts of data over satellite or slow cellular connections. Also, it enables systems to continue working offline even when a network connection is lost.
Data can be aggregated before sending it to a centralised site for further processing or storing. By getting rid of the distance and time, edge computing sends data to a centralized source fast. It has improved the speed and performance of applications and devices on edge.
Wrapping Up
Test Automation plays a massive role in IoT development. Thus, it’s essential not to downplay its importance as the benefits that come with it are immense.
Also, choosing the best database for your IoT solution is a challenging task. It’s easy to get confused since multiple options exist in the market today. Fortunately, the above steps can help you minimize your confusion.
Understand your needs to settle for the right choice. Don’t forget to consider aspects like the cost, licensing fees, and the location of the database.
