stevedunn / stringlytyped

Production Scaling

Scaling the stevedunn/stringlytyped project in production involves careful planning and implementation of techniques aimed at handling increased load. The following steps outline how to scale this project effectively, with detailed code examples provided to support the implementation.

Step 1: Optimize Performance with Benchmarking

The first step is to understand the performance characteristics of the application. It’s crucial to benchmark different operations to identify bottlenecks.

Use the following benchmarking setup to measure serialization and deserialization times:

[SimpleJob(RuntimeMoniker.Net461)]
[SimpleJob(RuntimeMoniker.NetCoreApp20)]
[SimpleJob(RuntimeMoniker.NetCoreApp21)]
[SimpleJob(RuntimeMoniker.Net50)]
[NativeMemoryProfiler]
[MemoryDiagnoser]
public class PersistenceBenchmarks
{
    [Benchmark]
    public string Serialising()
    {
        JsonSerializerOptions options = new JsonSerializerOptions
        {
            Converters = { new ValueObjectConverterFactory() }
        };
        Container containers = BuildContainer();

        return JsonSerializer.Serialize(containers, options);
    }

    [Benchmark]
    public Container Deserialising()
    {
        JsonSerializerOptions options = new JsonSerializerOptions
        {
            Converters = { new ValueObjectConverterFactory() }
        };

        Container container = BuildContainer();
        string s = JsonSerializer.Serialize(container, options);

        return JsonSerializer.Deserialize(s, options);
    }

    private Container BuildContainer()
    {
        var c = new Container();
        for (int j = 0; j < 100; j++)
        {
            c.Vo1_ints.Add(Vo_int_1.From(j));
            // Add similar entries for doubles and strings
        }

        return c;
    }
}

Use the results of these benchmarks to identify areas needing optimization, particularly in serialization/deserialization logic.

Step 2: Implement a Caching Strategy

To reduce the frequency of data serialization/deserialization during high-load scenarios, implement a caching layer. Utilize in-memory caching for immediate access to frequently used data.

public class CachingService
{
    private readonly MemoryCache _cache = new MemoryCache(new MemoryCacheOptions());

    public void Set(string key, object value, TimeSpan expiration)
    {
        _cache.Set(key, value, expiration);
    }

    public object Get(string key)
    {
        _cache.TryGetValue(key, out var value);
        return value;
    }
}

// Usage
CachingService cache = new CachingService();
string cacheKey = "some_key";
cache.Set(cacheKey, container, TimeSpan.FromMinutes(30));
var cachedValue = cache.Get(cacheKey);

Step 3: Load Testing and Capacity Planning

Before deploying at scale, conduct load testing to mimic realistic user behavior. Use tools like Apache JMeter or k6 to simulate requests. Measure application performance limits and identify maximum capacity based on observed data.

Step 4: Scaling Out with Distributed Systems

Consider deploying multiple instances of the stringlytyped service using a microservices architecture. Tools such as Docker and Kubernetes can help manage containerized deployments efficiently.

Example of a simple Dockerfile:

FROM mcr.microsoft.com/dotnet/aspnet:6.0 AS base
WORKDIR /app
EXPOSE 80

FROM mcr.microsoft.com/dotnet/sdk:6.0 AS build
WORKDIR /src
COPY ["StringlyTyped.csproj", "./"]
RUN dotnet restore "./StringlyTyped.csproj"
COPY . .
WORKDIR "/src/."
RUN dotnet build "StringlyTyped.csproj" -c Release -o /app/build

FROM build AS publish
RUN dotnet publish "StringlyTyped.csproj" -c Release -o /app/publish

FROM base AS final
WORKDIR /app
COPY --from=publish /app/publish .
ENTRYPOINT ["dotnet", "StringlyTyped.dll"]

Step 5: Monitoring and Logging

Implement application performance monitoring (APM) tools, such as Application Insights or Prometheus, to capture telemetry data in production. This enables proactive management of performance issues and analysis of system health.

Example configuration using Serilog for logging:

public class Program
{
    public static void Main(string[] args)
    {
        Log.Logger = new LoggerConfiguration()
            .MinimumLevel.Debug()
            .WriteTo.Console()
            .WriteTo.File("logs/log-.txt", rollingInterval: RollingInterval.Day)
            .CreateLogger();

        try
        {
            Log.Information("Starting up");
            CreateHostBuilder(args).Build().Run();
        }
        catch (Exception ex)
        {
            Log.Fatal(ex, "Application start-up failed");
        }
        finally
        {
            Log.CloseAndFlush();
        }
    }

    public static IHostBuilder CreateHostBuilder(string[] args) =>
        Host.CreateDefaultBuilder(args)
            .UseSerilog()
            .ConfigureWebHostDefaults(webBuilder => webBuilder.UseStartup<Startup>());
}

By implementing these techniques, developers can ensure that the stevedunn/stringlytyped project scales effectively in production, handling increased load and improving overall performance.

Sources