Great question—this is a frustrating edge case when you're stuck with in-memory tokens and can't modify server-side settings. Let's dive into actionable solutions that avoid dummy pre-request checks, don't require token persistence, and work within your constraints:

1. Enhance Token Refresh Logic with Error-Driven Retries #

Instead of checking for 401s upfront, modify your existing token validation to trigger a refresh only when you encounter a failure that suggests a server restart (like 401 Unauthorized or 5xx errors). Add a lightweight retry layer that automatically fetches a new token and retries the request once.

Here's how you could adjust your code:

private Token _currentToken;
private bool _recentFailureFlag;
private DateTime _lastFailureTime;

public async Task<ApiResponse> MakeAuthenticatedRequest()
{
    // First, check original expiration logic + recent failure signal
    bool shouldRefresh = _currentToken.ExpirationDate < DateTime.Now.AddMinutes(1) 
        || (_recentFailureFlag && DateTime.Now - _lastFailureTime < TimeSpan.FromMinutes(5));

    if (shouldRefresh)
    {
        _currentToken = GetToken();
        _recentFailureFlag = false; // Reset flag after successful refresh
    }

    try
    {
        var response = await SendRequestWithToken(_currentToken);
        _recentFailureFlag = false;
        return response;
    }
    catch (HttpRequestException ex) 
        when (ex.StatusCode == HttpStatusCode.Unauthorized || (int)ex.StatusCode >= 500)
    {
        // Mark potential server restart, then retry with fresh token
        _recentFailureFlag = true;
        _lastFailureTime = DateTime.Now;
        _currentToken = GetToken();
        return await SendRequestWithToken(_currentToken);
    }
}

This approach keeps your normal flow efficient (no unnecessary checks) while handling server restarts gracefully when they happen.

2. Add a Forced Token Refresh Interval #

Since your test environment uses an extremely long token expiry (19 years), you can safely add a periodic forced refresh to proactively avoid stale tokens after server restarts. Pick an interval that aligns with how often your server might restart (e.g., daily, every 8 hours).

Example adjustment to your existing check:

private DateTime _lastForcedRefresh = DateTime.MinValue;
private readonly TimeSpan _forcedRefreshWindow = TimeSpan.FromHours(24); // Tune based on your env

public void CheckAndRefreshToken()
{
    bool needsRefresh = _currentToken.ExpirationDate < DateTime.Now.AddMinutes(1)
        || DateTime.Now - _lastForcedRefresh > _forcedRefreshWindow;

    if (needsRefresh)
    {
        _currentToken = GetToken();
        _lastForcedRefresh = DateTime.Now;
    }
}

This is a low-effort fix—since you're already using a long expiry, the extra token requests will be negligible, and you'll avoid most server-restart-related token failures.

3. Use a Sliding Expiration Memory Cache #

Leverage an in-memory cache with sliding expiration to automatically refresh tokens if there's a lull in activity (which often coincides with server restarts). The cache will keep the token alive as long as requests are flowing, but refresh it if there's a gap long enough to risk a server restart.

Using .NET's MemoryCache as an example:

private IMemoryCache _tokenCache;
private const string TokenCacheKey = "ActiveOAuthToken";

public Token GetValidToken()
{
    if (!_tokenCache.TryGetValue(TokenCacheKey, out Token cachedToken)
        || cachedToken.ExpirationDate < DateTime.Now.AddMinutes(1))
    {
        cachedToken = GetToken();
        // Refresh token if no requests are made for 1 hour
        var cacheOptions = new MemoryCacheEntryOptions()
            .SetSlidingExpiration(TimeSpan.FromHours(1));
        _tokenCache.Set(TokenCacheKey, cachedToken, cacheOptions);
    }
    return cachedToken;
}

This combines your original expiry check with activity-based refresh, ensuring you never use a token that's been invalidated by a server restart during an idle period.

Final Notes #

All these solutions work without server-side changes or token persistence, and avoid the overhead of pre-request dummy checks. Choose the one that best fits your test environment's restart pattern:

• Error-driven retries are ideal if restarts are random and infrequent.
• Forced intervals work well if you can predict restart windows (e.g., nightly deployments).
• Sliding cache expiration is great for environments with unpredictable idle periods.

内容的提问来源于stack exchange，提问作者Sebastian Budka